Artykuły w czasopismach na temat „Mobile and static robots”
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Zhang, Sitong, i Tianyi Zhao. "Mobile Robot Path Planning in 2D Space: A Survey". Highlights in Science, Engineering and Technology 16 (10.11.2022): 279–89. http://dx.doi.org/10.54097/hset.v16i.2508.
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Robot path planning is task of navigating a mobile robot around a space in which lie a number of obstacles that have to be avoided. Path-planning can be static or dynamic.It is also an important primitive for autonomous mobile robots that lets robots find the shortest or otherwise optimal path between two points. Here we deal with static path-planning. We proposed 8 methods for path planning on this topic.
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Hirano, Tetsuro, Masato Ishikawa i Koichi Osuka. "Control and Development of Cylindrical Mobile Robot". Journal of Robotics and Mechatronics 25, nr 2 (20.04.2013): 392–99. http://dx.doi.org/10.20965/jrm.2013.p0392.
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Mobile robots are often exposed to various hazardous situations such as wet or dusty environments. However, it is easy for robots whose components are totally covered with a rigid shell to travel in such environments. For these robots, rolling is an effective way of locomotion. In this study, we focused on a rolling robot with a cylindrical shell to operate in such environments. We analyzed and developed the robot utilizing its interesting geometrical properties and established a control strategy for static locomotion.
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Güzel, Mehmet Serdar, Mehmet Kara i Mehmet Sıtkı Beyazkılıç. "An adaptive framework for mobile robot navigation". Adaptive Behavior 25, nr 1 (23.01.2017): 30–39. http://dx.doi.org/10.1177/1059712316685875.
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Collective behaviours observed in nature bring new methodologies in proposing control algorithms for robot groups to perform a variety of complex tasks. In this article, an adaptive algorithm, allowing the safe navigation of a group of robots in a collective manner, is proposed. The algorithm, inspired from the adaptive particle swarm optimization technique, proposes an efficient control approach to overcome both static and moving obstacles. Accordingly, compared to the conventional particle swarm optimization algorithm, the proposed system allows a robot or group of robots (swarm) to complete the goal while avoiding static and moving obstacles as well as dynamic targets in a safe and collective manner. The simulation results verify the overall performance and reliability of the proposed system.
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Fiedeń, Mateusz, i Jacek Bałchanowski. "A Mobile Robot with Omnidirectional Tracks—Design and Experimental Research". Applied Sciences 11, nr 24 (11.12.2021): 11778. http://dx.doi.org/10.3390/app112411778.
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This article deals with the design and testing of mobile robots equipped with drive systems based on omnidirectional tracks. These are new mobile systems that combine the advantages of a typical track drive with the advantages of systems equipped with omnidirectional Mecanum wheels. The omnidirectional tracks allow the robot to move in any direction without having to change the orientation of its body. The mobile robot market (automated construction machinery, mobile handle robots, mobile platforms, etc.) constantly calls for improvements in the manoeuvrability of vehicles. Omnidirectional drive technology can meet such requirements. The main aim of the work is to create a mobile robot that is capable of omnidirectional movement over different terrains, and also to conduct an experimental study of the robot’s operation. The paper presents the construction and principles of operation of a small robot equipped with omnidirectional tracks. The robot’s construction and control system, and also a prototype made with FDM technology, are described. The trajectory parameters of the robot’s operation along the main and transverse axes were measured on a test stand equipped with a vision-based measurement system. The results of the experimental research became the basis for the development and experimental verification of a static method of correcting deviations in movement trajectory.
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Guo, Li Xin, Qiu Ye Huang, Hua Long Xie, Jin Li Li i Zhao Wen Wang. "Localization and Control System of Mobile Robot Based on Wireless Sensor Network". Applied Mechanics and Materials 16-19 (październik 2009): 1133–37. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.1133.
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The localization of mobile robots is one of important problems for navigation of mobile robots. The wireless sensor network, i.e., Cricket wireless localization technology, was used to obtain motive condition of mobile objects in this study. The information transmission between the Cricket localization system and mobile robot system was achieved for localization, navigation and control of the mobile object. The errors of localization sampling data of the Cricket localization system vary within 3cm in a static condition. The Cricket localization system can meet the navigation requirement of the mobile robots.
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Gulevskiy, V. V. "ON QUASI-STATIC MODES OF MOTION OF UNDERWATER MOBILE ROBOTS WITH ANCHOR-ROPE-TRACK DRIVES". IZVESTIA VOLGOGRAD STATE TECHNICAL UNIVERSITY, nr 9(256) (15.09.2021): 26–31. http://dx.doi.org/10.35211/1990-5297-2021-9-256-26-31.
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A method for calculating mobile robots with anchor-cable-tracked drives is considered. The influence of the mass-geometric characteristics of a mobile robot on the stability of its movement in quasi-static modes of movement along the bottom of a reservoir is considered.
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Rodríguez-Molina, Alejandro, Axel Herroz-Herrera, Mario Aldape-Pérez, Geovanni Flores-Caballero i Jarvin Alberto Antón-Vargas. "Dynamic Path Planning for the Differential Drive Mobile Robot Based on Online Metaheuristic Optimization". Mathematics 10, nr 21 (27.10.2022): 3990. http://dx.doi.org/10.3390/math10213990.
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Mobile robots are relevant dynamic systems in recent applications. Path planning is an essential task for these robots since it allows them to move from one location to another safely and at an affordable cost. Path planning has been studied extensively for static scenarios. However, when the scenarios are dynamic, research is limited due to the complexity and high cost of continuously re-planning the robot’s movements to ensure its safety. This paper proposes a new, simple, reliable, and affordable method to plan safe and optimized paths for differential mobile robots in dynamic scenarios. The method is based on the online re-optimization of the static parameters in the state-of-the-art deterministic path planner Bug0. Due to the complexity of the dynamic path planning problem, a metaheuristic optimization approach is adopted. This approach utilizes metaheuristics from evolutionary computation and swarm intelligence to find the Bug0 parameters when the mobile robot is approaching an obstacle. The proposal is tested in simulation, and well-known metaheuristic methods are compared, including Differential Evolution (DE), the Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). The dynamic planner based on PSO generates paths with the best performances. In addition, the results of the PSO-based planner are compared with different Bug0 configurations, and the former is shown to be significantly better.
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Lin, Hung-Hsing, i Ching-Chih Tsai. "Improved global localization of an indoor mobile robot via fuzzy extended information filtering". Robotica 26, nr 2 (marzec 2008): 241–54. http://dx.doi.org/10.1017/s0263574707003876.
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SUMMARYGlobal localization of mobile robots has been well studied using the extended Kalman filter (EKF) method. This paper presents a fuzzy extended information filtering (FEIF) approach to improving global localization of an indoor autonomous mobile robot with ultrasonic and laser scanning measurements. A real-time FEIF algorithm is proposed to improve accuracy of static global pose estimation via multiple ultrasonic data. By fusing odometric, ultrasonic, and laser scanning data, a real-time FEIF-based pose tracking algorithm is developed to improve accuracy of the robot's continuous poses. Several experimental results are performed to confirm the efficacy of the proposed methods.
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Dewi, Tresna, Naoki Uchiyama, Shigenori Sano i Hiroki Takahashi. "Swarm Robot Control for Human Services and Moving Rehabilitation by Sensor Fusion". Journal of Robotics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/278659.
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A current trend in robotics is fusing different types of sensors having different characteristics to improve the performance of a robot system and also benefit from the reduced cost of sensors. One type of robot that requires sensor fusion for its application is the service robot. To achieve better performance, several service robots are preferred to work together, and, hence, this paper concentrates on swarm service robots. Swarm service mobile robots operating within a fixed area need to cope with dynamic changes in the environment, and they must also be capable of avoiding dynamic and static obstacles. This study applies sensor fusion and swarm concept for service mobile robots in human services and rehabilitation environment. The swarm robots follow the human moving trajectory to provide support to human moving and perform several tasks required in their living environment. This study applies a reference control and proportional-integral (PI) control for the obstacle avoidance function. Various computer simulations are performed to verify the effectiveness of the proposed method.
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Conceicao, Andre G. S., Mariane D. Correia i Luciana Martinez. "Modeling and friction estimation for wheeled omnidirectional mobile robots". Robotica 34, nr 9 (12.02.2015): 2140–50. http://dx.doi.org/10.1017/s0263574715000065.
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SUMMARYIn this study, a model for wheeled mobile robots that includes a static friction model in the force balance at the robot's center of mass is presented. Additionally, a least-squares method to linearly combine functions is proposed to estimate the friction coefficients. The experimental and simulation results are discussed to demonstrate the effectiveness of this approach in indoor environments for two floor types.
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Ozaki, Koichi, Hajime Asama, Yoshiki Ishida, Akihiro Matsumoto i Isao Endo. "Collision Avoidance Using Communication between Autonomous Mobile Robots". Journal of Robotics and Mechatronics 8, nr 5 (20.10.1996): 459–66. http://dx.doi.org/10.20965/jrm.1996.p0459.
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This paper addresses mutual collision avoidance between multiple mobile robots based on a layered strategy. In this Strategy, static motion generation and dynamic motion generation of several levels are provided , and a proper level of dynamic motion generation is selected for mutual collision avoidance according to the complexity of the situation. We have implemented two typical methods in the layered strategy , which are rules-based local collision avoidance and negotiation-based global one using communication. In each method, a robot detects collision and applies as a local method as possible. Experimental results show two actual mobile robots can achieve mutual collision avoidance based on the layered strategy.
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Tsilomitrou, Ourania, i Anthony Tzes. "Mobile Data-Mule Optimal Path Planning for Wireless Sensor Networks". Applied Sciences 12, nr 1 (27.12.2021): 247. http://dx.doi.org/10.3390/app12010247.
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This article is concerned with collecting stored sensor data from a static Wireless Sensor Network utilizing a group of mobile robots that act as data mules. In this scenario, the static sensor nodes’ locations are known a priori, and the overall optimization problem is formulated as a variation of the Traveling Salesman Subset-tour Problem (TSSP). The constraints that are taken into account include: (a) the pairwise distance between static nodes, (b) the maximum time interval between consecutive visits of each static node, (c) the service time that is required for the collection of the sensor data from the mobile element that visits this sensor node, and (d) the energy efficiency for the mobile nodes. The optimal mobile robot paths are computed using an enhanced Mobile Element Scheduling scheme. This scheme extracts the sequential paths of the mobile elements in an attempt to eliminate any sensor data loss.
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Alkhaleeli, Alaq, i E. Lukyanov. "MOTION CONTROL OF A WHEELED MOBILE ROBOT BASED ON SIMULATION". Bulletin of Belgorod State Technological University named after. V. G. Shukhov 7, nr 8 (16.08.2022): 112–21. http://dx.doi.org/10.34031/2071-7318-2022-7-8-112-121.
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A mobile robot is a complex system capable of receiving information about the outside world and using it to move safely in a purposeful way. The work information subsystem can determine its position using sensors, as well as the location of static and dynamic objects in the workspace. The robot's movement to the target point is carried out according to various algorithms. These algorithms implement various methods of planning the trajectory of movement to the target point: to prevent the robot from colliding with barriers, to reduce the travel time and distance traveled to save battery power. Mobile robots can function in a dynamic environment with a significant degree of uncertainty. One of the main tasks of a mobile robot is planning trajectories by controlling the movement of the robot to reach target point. This article proposes a method for planning trajectory of a mobile robot by controlling its movement. The method is based on simulation of the movement of a mobile robot in an environment with fixed and movable barriers. It is assumed that the direction of dynamic obstacles can change randomly.
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Rashid, Abdulmuttalib, Abduladhem Ali i Mattia Frasca. "Polygon Shape Formation for Multi-Mobile Robots in a Global Knowledge Environment". Iraqi Journal for Electrical and Electronic Engineering 15, nr 1 (1.06.2019): 76–88. http://dx.doi.org/10.37917/ijeee.15.1.8.
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In coordination of a group of mobile robots in a real environment, the formation is an important task. Multimobile robot formations in global knowledge environments are achieved using small robots with small hardware capabilities. To perform formation, localization, orientation, path planning and obstacle and collision avoidance should be accomplished. Finally, several static and dynamic strategies for polygon shape formation are implemented. For these formations minimizing the energy spent by the robots or the time for achieving the task, have been investigated. These strategies have better efficiency in completing the formation, since they use the cluster matching algorithm instead of the triangulation algorithm.
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Ravankar, Abhijeet, Ankit Ravankar, Yukinori Kobayashi, Yohei Hoshino i Chao-Chung Peng. "Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges". Sensors 18, nr 9 (19.09.2018): 3170. http://dx.doi.org/10.3390/s18093170.
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Robot navigation is an indispensable component of any mobile service robot. Many path planning algorithms generate a path which has many sharp or angular turns. Such paths are not fit for mobile robot as it has to slow down at these sharp turns. These robots could be carrying delicate, dangerous, or precious items and executing these sharp turns may not be feasible kinematically. On the contrary, smooth trajectories are often desired for robot motion and must be generated while considering the static and dynamic obstacles and other constraints like feasible curvature, robot and lane dimensions, and speed. The aim of this paper is to succinctly summarize and review the path smoothing techniques in robot navigation and discuss the challenges and future trends. Both autonomous mobile robots and autonomous vehicles (outdoor robots or self-driving cars) are discussed. The state-of-the-art algorithms are broadly classified into different categories and each approach is introduced briefly with necessary background, merits, and drawbacks. Finally, the paper discusses the current and future challenges in optimal trajectory generation and smoothing research.
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Xu, He, X. Z. Gao, Yan Xu, Kaifeng Wang, Hongpeng Yu, Zhen Li, Khalil Alipour i Ozoemena Anthony Ani. "Continuous mobility of mobile robots with a special ability for overcoming driving failure on rough terrain". Robotica 35, nr 10 (31.08.2016): 2076–96. http://dx.doi.org/10.1017/s0263574716000606.
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SUMMARYFor wheeled mobile robots moving in rough terrains or uncertain environments, driving failure will be encountered when trafficability failure occurs. Continuous mobility of mobile robots with special ability for overcoming driving failure on rough terrain has rarely been considered. This study was conducted using a four-wheel-steering and four-wheel-driving mobile robot equipped with a binocular visual system. First, quasi-static force analysis is carried out to understand the effects of different driving-failure modes on the mobile robot while moving on rough terrain. Secondly, to make the best of the rest of the driving force, robot configuration transformation is employed to select the optimal configuration that can overcome the driving failure. Thirdly, sliding mode control based on back-stepping is adopted to enable the robot achieve continuous trajectory tracking with visual feedback. Finally, the efficacy of the presented approach is verified by simulations and experiments.
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BARRIÈRE, LALI, PAOLA FLOCCHINI, EDUARDO MESA-BARRAMEDA i NICOLA SANTORO. "UNIFORM SCATTERING OF AUTONOMOUS MOBILE ROBOTS IN A GRID". International Journal of Foundations of Computer Science 22, nr 03 (kwiecień 2011): 679–97. http://dx.doi.org/10.1142/s0129054111008295.
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We consider the uniform scattering problem for a set of autonomous mobile robots deployed in a grid network: starting from an arbitrary placement in the grid, using purely localized computations, the robots must move so to reach in finite time a state of static equilibrium in which they cover uniformly the grid. The theoretical quest is on determining the minimal capabilities needed by the robots to solve the problem. We prove that uniform scattering is indeed possible even for very weak robots. The proof is constructive. We present a provably correct protocol for uniform self-deployment in a grid. The protocol is fully localized, collision-free, and it makes minimal assumptions; in particular: (1) it does not require any direct or explicit communication between robots; (2) it makes no assumption on robots synchronization or timing, hence the robots can be fully asynchronous in all their actions; (3) it requires only a limited visibility range; (4) it uses at each robot only a constant size memory, hence computationally the robots can be simple Finite-State Machines; (5) it does not need a global localization system but only orientation in the grid (e.g., a compass); (6) it does not require identifiers, hence the robots can be anonymous and totally identical.
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Lee, Min-Fan Ricky, i Sharfiden Hassen Yusuf. "Mobile Robot Navigation Using Deep Reinforcement Learning". Processes 10, nr 12 (19.12.2022): 2748. http://dx.doi.org/10.3390/pr10122748.
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Learning how to navigate autonomously in an unknown indoor environment without colliding with static and dynamic obstacles is important for mobile robots. The conventional mobile robot navigation system does not have the ability to learn autonomously. Unlike conventional approaches, this paper proposes an end-to-end approach that uses deep reinforcement learning for autonomous mobile robot navigation in an unknown environment. Two types of deep Q-learning agents, such as deep Q-network and double deep Q-network agents are proposed to enable the mobile robot to autonomously learn about collision avoidance and navigation capabilities in an unknown environment. For autonomous mobile robot navigation in an unknown environment, the process of detecting the target object is first carried out using a deep neural network model, and then the process of navigation to the target object is followed using the deep Q-network or double deep Q-network algorithm. The simulation results show that the mobile robot can autonomously navigate, recognize, and reach the target object location in an unknown environment without colliding with static and dynamic obstacles. Similar results are obtained in real-world experiments, but only with static obstacles. The DDQN agent outperforms the DQN agent in reaching the target object location in the test simulation by 5.06%.
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Tsung, Tsing Tshih, Nguyen Hoai i Thi Khanh Vy Tang. "Testing and Improvement of Static Performance of Proximity Sensor for a Mobile Robot". Key Engineering Materials 656-657 (lipiec 2015): 719–24. http://dx.doi.org/10.4028/www.scientific.net/kem.656-657.719.
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In recent years, mobile robot is one of the most interesting topics attracting scientists and factories. With breakthrough techniques in sensor, we can control a mobile robot more reliably. Besides, measuring at static state of the inductive proximity sensor is also necessary since the detective and navigation systems perform more accurately by information from the experiment by analyzing the signal. The purpose of this paper, the hand-made measurement system is used to verify the static performance with the type of aluminium and analyse the relationship between the output signal and the position of the sensor. All we know that the relationship of the static parameters can be determined such as: sensing distance, dimension of material, thickness of material, and so on. The measured data have shown the output signal of proximity sensor in the model and theory which is not identical. The results will provide some information about the different effects of position sensor and optimum operating range of a mobile robot. In addition, by comparing the results achieved, giving solutions to enhance the static performance of the proximity sensor for a mobile robot, such as: choosing of material thickness ranges which is suitable for the operation of a mobile robot, setting the proper sensing distance to be the most stable. This research aims to provide a secure and accurate signal for the control of mobile robots.
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Rendyansyah, Rendyansyah, Aditya P. P. Prasetyo i Sarmayanta Sembiring. "Voice Command Recognition for Movement Control of a 4-DoF Robot Arm". ELKHA 14, nr 2 (20.10.2022): 118. http://dx.doi.org/10.26418/elkha.v14i2.57556.
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Robots are widely used in industry. Robots generally have a control system or intelligence embedded in the processor. The robots consist of mobile mode, manipulator, and their combination. Mobile robots usually use wheels, and manipulator robots have limited degrees of freedom. Both have their respective advantages. Mobile robots are widely applied to environments with flat floor surfaces. The manipulator robots are applied to a static environment to produce, print, and cut material. In this study, the robot arm 4 Degree of Freedom (DoF) is integrated with a computer. The computer controls the whole system, where the operator can control the Robot based on voice commands. The operator's voice is one person only with different intonations. Voice command recognition uses the Mel-Frequency Cepstral Coefficients (MFCC) and Artificial Neural Networks (ANN) methods. The MFCC and ANN programs are processed in the computer, and the program output is sent to the Robot via serial communication. There are nine types of voice commands with different MFCC patterns. ANN training data for each command is 10 data, so the total becomes 90. In this experiment, the Robot can move according to voice commands given by the operator. Tests for each voice command are ten experiments, so the total experiment is 90 times with a success rate of 94%. There is only one operator, and experiments have not yet been carried out with the voices of several operators. The error occurred because there were several similar patterns during system testing.
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Engelbrecht, Duanne, Nico Steyn i Karim Djouani. "Adaptive Virtual Impedance Control of a Mobile Multi-Robot System". Robotics 10, nr 1 (21.01.2021): 19. http://dx.doi.org/10.3390/robotics10010019.
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The capabilities of collaborative robotics have transcended the conventional abilities of decentralised robots as it provides benefits such as scalability, flexibility and robustness. Collaborative robots can operate safely in complex human environments without being restricted by the safety cages or barriers that often accompany them. Collaborative robots can be used for various applications such as machine tending, packaging, process tasks and pick and place. This paper proposes an improvement of the current virtual impedance algorithm by developing an adaptive virtual impedance controlled mobile multi-robot system focused on dynamic obstacle avoidance with a controlled planar movement. The study includes the development of a mobile multi-robot platform whereby each robot plans a path individually without a supervisor. The proposed system would implement a two-layered hierarchy for robot path planning. The higher layer generates a trajectory from the current position to the desired position, and the lower layer develops a real-time strategy to follow the generated trajectory while avoiding static and dynamic obstacles. The key contribution of this paper is the adaptive virtual impedance controller for a multi-robot system that will maintain movement stability and improve the motion behaviour in a dynamic environment.
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Ahmad Dahalan, A’Qilah, Azali Saudi i Jumat Sulaiman. "Robot pathfinding with obstacle avoidance capabilities in a static indoor environment via TOR iterative method using harmonic potentials". ITM Web of Conferences 36 (2021): 04006. http://dx.doi.org/10.1051/itmconf/20213604006.
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Mobile robots are always in a state where they have to find a collision-free path in their environment from start to the target point. This study tries to solve the problem of mobile robot iteratively by using a numerical technique. It is based on potential field technique that was modelled using the Laplace’s equation to restrain the creation of a potential functions across regions in the mobile robot’s configuration space. The gradient formed by the potential field is then used to generate a path for the robot to advance through. The present paper proposes a Two-Parameter Over-Relaxation (TOR) iterative method that is used to solve Laplace’s equation for obtaining the potential field that is then utilized for finding path of the robot, thus solving the robot pathfinding problem. The experiment indicates that it is capable of producing a smooth path between the starting and target points through the use of a finite-difference technique. Furthermore, the simulation results show that this numerical approach executes quicker and provides a smoother trail than to the previous works, that includes Successive Over-Relaxation (SOR) and Accelerated Over-Relaxation (AOR) methods.
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Sukhoruchkina, O. M., i M. V. Progonnyi. "System Of The Intellectualized Video Monitoring for Goal-Directed Interaction with Autonomous Mobile Robot". Control Systems and Computers, nr 3 (299) (2022): 29–38. http://dx.doi.org/10.15407/csc.2022.03.029.
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Introduction. One of the conditions for increasing the autonomous capabilities of mobile robots is their awareness of the state of the environment in which they operate. A class of so-called indoor robots requires the timely acquisition of position data both on obstacle objects and goal interest objects for the robot actions. As a rule, the sources of data on surrounding objects are sensor devices of various types installed on the board of the robot. In modern robotics, such devices are rangefinders or scanners with various data acquisition principles and video cameras. It is images from the video cameras that contain the most complete information about the state of the mobile robot’s working room. But computer analysis and content interpretation of visual data require the development of appropriate information technologies. Successful software implementations of rather complex algorithms for visual object recognition and methods for determining these object positions relative to the room coordinate system, which were previously created as separate functional modules of the intelligent mobile robot control system, can be used to create other applied artificial intelligence systems. The formation of generalized images (models) of the environment and the states of the robot in it is important for the intelligent control system of autonomous mobile robots. Images from the robot’s onboard video camera are the most informative source of timely detection of the positions of static and dynamic objects in the robot’s working areas. Using additional information from an external video camera can not only increase the general situational awareness of an autonomous robot but also speed up the achievement of goal states, as long as the external video monitoring control system has an interface for goal-directed interaction with the mobile robot intelligent control system and conforming data structures for the representation of surrounding objects. The purpose of the article is to describe the results of the development of a control system of intellectualized video monitoring in the autonomous mobile robot working environment, as an additional external source of the object’s location data. Methods. 3D modeling of technical systems and spatial scenes, content interpretation of data, and object-oriented programming. Results. The functioning of the developed system of intellectualized video monitoring has been studied. Accuracy of the positions of static and dynamic objects obtained by this system both as a separate applied system of artificial intelligence and as an additional source of data on the presence and position of objects in the working room while interacting with an autonomous mobile robot has been estimated. Conclusions. The analysis of the functioning results of the system of intellectualized video monitoring which is intended for detecting objects and determining their positions in the room, and which is described in the article, shows that such a system can have a number of independent applications. Its most productive use is in the autonomous mobile robot working environment. Wide awareness of the autonomous mobile robot about the surrounding objects due to the interaction of two technical systems of artificial intelligence, namely, the intelligent control system of the mobile robot and the control system of the intellectualized video monitoring leads to the increase in the autonomous capabilities of the robot to perform complex tasks given by the user in a shorter time.
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Vasu, V., i K. Jyothi Kumar. "Optimal Path Planning of an Autonomous Mobile Robot Using Genetic Algorithm". Advanced Materials Research 488-489 (marzec 2012): 1747–51. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.1747.
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An autonomous Mobile Robot (AMR) is a machine able to extract information from its environment and move in a meaningful and purposeful manner. Robot Navigation and Obstacle avoidance are the most important problems in mobile robots. In the past, a number of soft computing algorithms have been designed by many researchers for robot navigation problems but very few are actually implementable because they haven’t considered robot size as parameter. This paper presents software simulation and hardware implementation of navigation of a mobile robot avoiding obstacles and selecting optimal path in a static environment using evolution based Genetic algorithms with robot size as a parameter in fitness function.
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Tang, Swee Ho, Che Fai Yeong i Eileen Lee Ming Su. "Comparison between Waveform and Bug Path Planning Algorithm for Mobile Robot". Applied Mechanics and Materials 607 (lipiec 2014): 774–77. http://dx.doi.org/10.4028/www.scientific.net/amm.607.774.
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Mobile robots frequently find themselves in a circumstance where they need to find a trajectory to another position in their environment, subject to constraints postured by obstacles and the capabilities of the robot itself. This study compared path planning algorithms for mobile robots to move efficiently in a collision free grid based static environment. Two algorithms have been selected to do the comparison namely wavefront algorithm and bug algorithm. The wavefront algorithm involves a breadth-first search of the graph beginning at the goal position until it reaches the start position. The bug algorithm uses obstacles borders as guidance toward a goal with restricted details about the environment. The algorithms are compared in terms of parameters such as execution time of the algorithm and planned path length by using Player/Stage simulation software. Results shown that wavefront algorithm is a better path planning algorithm compared to bug algorithm in static environment.
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Jawad, Muna Mohammed, i Esraa Adnan Hadi. "A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots". Journal of Engineering 25, nr 6 (31.05.2019): 83–100. http://dx.doi.org/10.31026/j.eng.2019.06.07.
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In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot. Simulation results, which carried out using MATLAB 2014 environment, show the validity of the kinematic model for Nonholonomic mobile robot and demonstration that the proposed algorithm perform better than original PSO and FF algorithms under the same environmental constraints by providing the smoothness velocity and shortest path for each mobile robot.
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Hosseininejad, Seyedhadi, i Chitra Dadkhah. "Mobile robot path planning in dynamic environment based on cuckoo optimization algorithm". International Journal of Advanced Robotic Systems 16, nr 2 (1.03.2019): 172988141983957. http://dx.doi.org/10.1177/1729881419839575.
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Nowadays, the usage of autonomous mobile robots that fulfill various activities in enormous number of applications without human’s interference in a dynamic environment are thriving. A dynamic environment is the robot’s environment which is comprised of some static obstacles as well as several movable obstacles that their quantity and location change randomly through the time. Efficient path planning is one the significant necessities of these kind of robots to do their tasks effectively. Mobile robot path planning in a dynamic environment is finding a shortest possible path from an arbitrary starting point toward a desired goal point which needs to be safe (obstacle avoidance) and smooth as well as possible. To achieve this target, simultaneously satisfying a collection of certain constraints including the shortest, smooth, and collision free path is required. Therefore, this issue can be considered as an optimization problem, consequently solved via optimization algorithms. In this article, a new method based on cuckoo optimization algorithm is proposed for solving the mobile robot path planning problem in a dynamic environment. Furthermore, to diminish the computational complexity, the feature vector is also optimized (i.e. reduced in dimension) via a new proposed technique. The simulation results show the performance of proposed algorithm in finding a short, safe, smooth, and collision free path in different environment conditions.
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Feng, Maria Q., Takashi Kawamura i Takayuki Tanaka. "Parallel Bicycles and Their Applications". Journal of Robotics and Mechatronics 26, nr 1 (20.02.2014): 9–14. http://dx.doi.org/10.20965/jrm.2014.p0009.
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This paper describes the successful research and development (R&D) of parallel bicycles (PB robots) including six prototypes created by the authors and their applications to personal vehicles. The first, developed in 1986, consists of a pair of coaxial wheels and an inverted pendulum on the wheel axis. Since then, the authors have carried out fundamental and practical studies on static/dynamic posture stabilization control, dynamic movement, and slope and stair ascent/descent. The PB robot control mechanism has recently been applied to educational robots, mobile humanoid robots, and personal vehicles. This paper also discusses personal vehicles commercialized as an application of the PB robots.
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Ajeil, Fatin Hassan, Ibraheem Kasim Ibraheem, Ahmad Taher Azar i Amjad J. Humaidi. "Grid-Based Mobile Robot Path Planning Using Aging-Based Ant Colony Optimization Algorithm in Static and Dynamic Environments". Sensors 20, nr 7 (28.03.2020): 1880. http://dx.doi.org/10.3390/s20071880.
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Planning an optimal path for a mobile robot is a complicated problem as it allows the mobile robots to navigate autonomously by following the safest and shortest path between starting and goal points. The present work deals with the design of intelligent path planning algorithms for a mobile robot in static and dynamic environments based on swarm intelligence optimization. A modification based on the age of the ant is introduced to standard ant colony optimization, called aging-based ant colony optimization (ABACO). The ABACO was implemented in association with grid-based modeling for the static and dynamic environments to solve the path planning problem. The simulations are run in the MATLAB environment to test the validity of the proposed algorithms. Simulations showed that the proposed path planning algorithms result in superior performance by finding the shortest and the most free-collision path under various static and dynamic scenarios. Furthermore, the superiority of the proposed algorithms was proved through comparisons with other traditional path planning algorithms with different static environments.
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Hani, Umme, i Lubna Moin. "Realtime autonomous navigation in V-Rep based static and dynamic environment using EKF-SLAM". IAES International Journal of Robotics and Automation (IJRA) 10, nr 4 (1.12.2021): 296. http://dx.doi.org/10.11591/ijra.v10i4.pp296-307.
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<p>Localization in an autonomous mobile robot allows it to operate autonomously in an unknown and unpredictable environment with the ability to determine its position and heading. Simultaneous localization and mapping (SLAM) are introduced to solve the problem where no prior information about the environment is available either static or dynamic to achieve standard map-based localization. The primary focus of this research is autonomous mobile robot navigation using the extended Kalman filter (EKF)-SLAM environment modeling technique which provides higher accuracy and reliability in mobile robot localization and mapping results. In this paper, EKF-SLAM performance is verified by simulations performed in a static and dynamic environment designed in V-REP i.e., 3D Robot simulation environment. In this work SLAM problem of two-wheeled differential drive robot i.e., Pioneer 3-DX in indoor static and dynamic environment integrated with Laser range finder i.e., Hokuyo URG-04LX- UG01, LIDAR, and Ultrasonic sensors is solved. EKF-SLAM scripts are developed using MATLAB that is linked to V-REP via remote API feature to evaluate EKF-SLAM performance. The reached results confirm the EKF- SLAM is a reliable approach for real-time autonomous navigation for mobile robots in comparison to other techniques.</p>
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DAS, SUBIR KUMAR. "Local Path Planning of Mobile Robot Using Critical-PointBug Algorithm Avoiding Static Obstacles". IAES International Journal of Robotics and Automation (IJRA) 5, nr 3 (1.09.2016): 182. http://dx.doi.org/10.11591/ijra.v5i3.pp182-189.
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<p align="left">Path planning is an essential task for the navigation of Autonomous Mobile Robot. This is one of the basic problems in robotics. Path planning algorithms are classified as global or local, depending on the knowledge of surrounding environment. In local path planning, the environment is unknown to the robot, and sensors are used to detect the obstacles and to avoid collision. Bug algorithms are one of the frequently used path planning algorithms where a mobile robot moves to the target by detecting the nearest obstacle and avoiding it with limited information about the environment. This proposed Critical-PointBug algorithm, is a new Bug algorithm for path planning of mobile robots. This algorithm tries to minimize traversal of obstacle border by searching few important points on the boundary of obstacle area as a rotation point to goal and end with a complete path from source to goal.</p>
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Chen, Li Jia, He Jin, Jin Ke Bai i Hai Tao Mao. "Path Planning for Mobile Robots in 3D Dynamic Environments". Advanced Materials Research 403-408 (listopad 2011): 1401–4. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.1401.
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Aiming at the robustness of the path planning of mobile robots in the 3D dynamic environment, an improved ARF (Artificial Potential Field) based path planning algorithm is proposed in this paper. Supposing that all the obstacles move regularly and the robot is on uniform motion in a grid 3D environment. Firstly, the algorithm computes the future statuses of the environment, such as the coordinate of all the obstacles and the goal, until a time step T in which there is at least one route between the start and goal. T is obtained by BFS (Breadth First Search) and environment configuration parameters. Secondly, because in every time step the environment can be consider as being static, ARF is used to determine the potential value of every space position in each time step. Finally, a route along the lowest potential values is found for the robot from the start to goal. Simulation results show that the algorithm makes the robot avoid obstacles effectively and reach the goal safely.
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Nordin, Nur Amira Atika, Nazatul Aini Abd Majid i Noor Faridatul Ainun Zainal. "Mobile augmented reality using 3D ruler in a robotic educational module to promote STEM learning". Bulletin of Electrical Engineering and Informatics 9, nr 6 (1.12.2020): 2499–506. http://dx.doi.org/10.11591/eei.v9i6.2235.
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Robotics education is gaining popularity among school children in line with the government desire to promote creative thinking in students through STEM based activities. However, the robots for educational games are usually made up of components and its description is usually one-way and static. Additionally, students find it difficult to visualize distances from robot movements when playing educational robotic games. Augmented reality (AR) technology is a viable tool to connect between in-context information and physical activities. The objective of this research is to design and develop an AR based application that can visualize the distance between two robots for supporting learning process in a game-based module. The application consists of three parts; the first part use AR in identification of components related to robots, while the second part involves the addition of real-time visualization in the form of AR, enabling students to learn the distance from the robot's movements. The third part used AR in providing the description of the robotic games through videos. The development of the application is based on the Agile model. The results show that the application has received positive feedbacks from students as it can increase their interest in playing robotic educational games.
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Cosic, Aleksandar, Marko Susic, Stevica Graovac i Dusko Katic. "An algorithm for formation control of mobile robots". Serbian Journal of Electrical Engineering 10, nr 1 (2013): 59–72. http://dx.doi.org/10.2298/sjee1301059c.
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Solution of the formation guidance in structured static environments is presented in this paper. It is assumed that high level planner is available, which generates collision free trajectory for the leader robot. Leader robot is forced to track generated trajectory, while followers? trajectories are generated based on the trajectory realized by the real leader. Real environments contain large number of static obstacles, which can be arbitrarily positioned. Hence, formation switching becomes necessary in cases when followers can collide with obstacles. In order to ensure trajectory tracking, as well as object avoidance, control structure with several controllers of different roles (trajectory tracking, obstacle avoiding, vehicle avoiding and combined controller) has been adopted. Kinematic model of differentially driven two-wheeled mobile robot is assumed. Simulation results show the efficiency of the proposed approach.
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Lerke, Otto, i Volker Schwieger. "Analysis of a kinematic real-time robotic total station network for robot control". Journal of Applied Geodesy 15, nr 3 (24.06.2021): 169–88. http://dx.doi.org/10.1515/jag-2021-0016.
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Abstract The use of robots is widespread in the field of construction nowadays. Robots may be mobile or static depending on the specific task or application. One of the major challenges when implementing mobile robots is localisation. In the field of robotics, localisation is often performed in a relative sense, however some applications require absolute localisation. In order to provide absolute positions, appropriate sensors such as Global Navigation Satellite Systems (GNSS) or total stations can be employed. The underlying task is embedded within the Germany´s Excellence Strategy “Integrative Computational Design and Construction for Architecture (IntCDC)” funded by the German Research Foundation (DFG). The specific sub-project deals with issues of robot-robot collaboration and specifically aims the provision of absolute position and orientation, designated as pose, of a mobile construction robot. The determined pose information supports different control loops of the robot including automated driving, steering and tool operations. The choice of the sensor system favoured a robotic total station (RTS), because of its real-time capability and measurement accuracy. The measurement system is coupled with an Inertial Measurement Unit (IMU) for orientation. To counteract line-of-sight interference between the RTS and the target, the contribution proposes the use of a network of four spatially evenly distributed RTSs. The quality characteristics of different pose determination procedures of a mobile construction robot are investigated using methods from the geodetic network theory. Conclusions about accuracy and reliability distribution across the construction site are presented numerically and graphically.
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Imaoka, Noriaki, Kazuma Kitazawa, Mitsuhiro Kamezaki, Shigeki Sugano i Takeshi Ando. "Autonomous Mobile Robot Moving Through Static Crowd: Arm with One-DoF and Hand with Involute Shape to Maneuver Human Position". Journal of Robotics and Mechatronics 32, nr 1 (20.02.2020): 59–67. http://dx.doi.org/10.20965/jrm.2020.p0059.
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Owing to manpower shortages, robots are expected to be increasingly integrated into society in the future. Moreover, robots will be required to navigate through crowded environments. Thus, we proposed a new method of autonomous movement compatible with physical contact signaling used by humans. The method of contact was investigated before using an arm with six degrees of freedom (DoF), which increases the cost of the robot. In this paper, we propose a novel method of navigating through a human crowd by using a conventional driving system for autonomous mobile robots and an involute-shaped hand with an one-DoF arm. Finally, the effectiveness of the method was confirmed experimentally.
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Wang, Lu, Tao Zhang, Hiroatsu Fukuda i Yi Leng. "Research on the Application of Mobile Robot in Timber Structure Architecture". Sustainability 14, nr 8 (13.04.2022): 4681. http://dx.doi.org/10.3390/su14084681.
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The involvement of robots in building construction is already a global trend. Compared with the current stage of construction in which a large number of people are involved, the stability of the robot construction process will greatly affect the construction efficiency and construction accuracy, thus (1) reducing the impact on the environment, hence saving natural resources with other obvious advantages of natural environmental benefits, and (2) reducing construction costs, therefore reducing the economic and environmental benefits of artificial use. This paper proposes a wooden building construction method using a mobile robot, explores the assembly of continuous building components that exceed the robot’s static workspace, and completes a simulated construction experiment of a wooden building using this construction method. The experiment was used as a basis to address (1) innovations in the way a wooden building is erected that satisfy the construction logic of the mobile robot, and (2) the ability of the mobile robot to accurately assemble building components in space, including the ability to align them with existing components on site. Ultimately, the completion of this experiment and its construction evaluation demonstrated the superiority of mobile robot construction over manual construction in terms of reduced manual use and increased construction efficiency.
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Molina-Leal, Alejandra, Alfonso Gómez-Espinosa, Jesús Arturo Escobedo Cabello, Enrique Cuan-Urquizo i Sergio R. Cruz-Ramírez. "Trajectory Planning for a Mobile Robot in a Dynamic Environment Using an LSTM Neural Network". Applied Sciences 11, nr 22 (12.11.2021): 10689. http://dx.doi.org/10.3390/app112210689.
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Autonomous mobile robots are an important focus of current research due to the advantages they bring to the industry, such as performing dangerous tasks with greater precision than humans. An autonomous mobile robot must be able to generate a collision-free trajectory while avoiding static and dynamic obstacles from the specified start location to the target location. Machine learning, a sub-field of artificial intelligence, is applied to create a Long Short-Term Memory (LSTM) neural network that is implemented and executed to allow a mobile robot to find the trajectory between two points and navigate while avoiding a dynamic obstacle. The input of the network is the distance between the mobile robot and the obstacles thrown by the LiDAR sensor, the desired target location, and the mobile robot’s location with respect to the odometry reference frame. Using the model to learn the mapping between input and output in the sample data, the linear and angular velocity of the mobile robot are obtained. The mobile robot and its dynamic environment are simulated in Gazebo, which is an open-source 3D robotics simulator. Gazebo can be synchronized with ROS (Robot Operating System). The computational experiments show that the network model can plan a safe navigation path in a dynamic environment. The best test accuracy obtained was 99.24%, where the model can generalize other trajectories for which it was not specifically trained within a 15 cm radius of a trained destination position.
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AL -Nayar, Muna M., Khulood E. Dagher i Esraa A. Hadi. "A COMPARATIVE STUDY FOR WHEELED MOBILE ROBOT PATH PLANNING BASED ON MODIFIED INTELLIGENT ALGORITHMS". IRAQI JOURNAL FOR MECHANICAL AND MATERIALS ENGINEERING 19, nr 1 (8.03.2019): 60–74. http://dx.doi.org/10.32852/iqjfmme.v19i1.266.
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From the time being, there are even instances for application of mobile robots in our lifelike in home, schools, hospitals, etc. The goal of this paper is to plan a path and minimizing thepath lengths with obstacles avoidance for a mobile robot in static environment. In this work wedepict the issue of off-line wheeled mobile robot (WMR) path planning, which best route forwheeled mobile robot from a start point to a target at a plane environment represented by 2-Dwork space. A modified optimization technique to solve the problem of path planning problemusing particle swarm optimization (PSO) method is given. PSO is a swarm intelligence basedstochastic optimization technique which imitate the social behavior of fish schooling or birdflocking, was applied to locate the optimum route for mobile robot so as to reach a target.Simulation results, which executed using MATLAB 2014 programming language, confirmedthat the suggested algorithm outperforms the standard version of PSO algorithm with the sameenvironment conditions by providing the shortest path for mobile robot.
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Schjørring, Allan, Amalia Lelia Cretu-Sircu, Ignacio Rodriguez, Peter Cederholm, Gilberto Berardinelli i Preben Mogensen. "Performance Evaluation of a UWB Positioning System Applied to Static and Mobile Use Cases in Industrial Scenarios". Electronics 11, nr 20 (13.10.2022): 3294. http://dx.doi.org/10.3390/electronics11203294.
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Indoor positioning systems are essential in the industrial domain for optimized production and safe operation of mobile elements, such as mobile robots, especially in the presence of static machinery and human operators. In this paper, we assess the performance of a commercial UWB radio-based positioning system deployed in a realistic industrial scenario, considering both static and mobile use cases. Our goal is to characterize the accuracy of this system in the context of industrial use cases and applications. For the static case, an extensive analysis was presented based on measurements performed at 72 measurement positions at 3 different heights (above, at similar a level to, and below the average clutter level) in different industrial clutter conditions (open and cluttered spaces). The extensive analysis in the mobile case considered several runs of a route covered by an autonomous mobile robot equipped with multiple tags in different positions. The results indicate that a similar degree of accuracy with a median 2D positioning error smaller than 20 cm is possible in both static and mobile conditions with an optimized anchor deployment. The paper provides a complete statistical characterization of the system’s accuracy and addresses the multiple deployment trade-offs and system dynamics observed for the different configurations.
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Saunders, Joe, Chrystopher L. Nehaniv i Kerstin Dautenhahn. "Experimental comparisons of observational learning mechanisms for movement imitation in mobile robots". Interaction Studies 8, nr 2 (19.06.2007): 307–35. http://dx.doi.org/10.1075/is.8.2.07sau.
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Research into robotic social learning, especially that concerned with imitation, often focuses at differing ends of a spectrum from observational learning at one end to following or matched-dependent behaviour at the other. We study the implications and differences that arise when carrying out experiments both at the extremes and within this spectrum. Physical Khepera robots with minimal sensory capabilities are used, and after training, experiments are carried out where an imitating robot perceives the dynamic movement behaviours of another model robot carrying a light source. It learns the movement behaviour of the model by either statically observing the model, dynamically observing the model or by following the model. It finally re-enacts the learnt behaviour. We compare the results of these re-enactments and illustrate the differences and trade-offs that arise between static observational and reactive following learning methods. We also consider circumstances where, for this robotic embodiment, dynamic observation has both advantages and disadvantages when compared to static observation. We conclude by discussing the implications that arise from using and combining these types of social learning.
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Abed, Mustafa S., Omar F. Lutfy i Qusay F. Al-Doori. "Online Path Planning of Mobile Robots Based on African Vultures Optimization Algorithm in Unknown Environments". Journal Européen des Systèmes Automatisés 55, nr 3 (30.06.2022): 405–12. http://dx.doi.org/10.18280/jesa.550313.
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Autonomous mobile robots developed using metaheuristic algorithms are increasingly becoming a hot topic in control and computer sciences. Specifically, finding the shortest root to the goal and avoiding hurdles are current subjects of autonomous mobile robots. The main drawbacks of classic methods are the incapacity to move the robot in a dynamic and unknown environment, deadlock in a local minimum and complicated environments, and incapacity to foretell the speed vector of obstacles and non-optimality of the route. This article exhibits a recent path planning approach that utilizes the African Vultures Optimization (AVOA) for navigation of the mobile robot in static and dynamic unknown environments with a dynamic target. The proposed online optimization approach is used in three different environments including an environment with unknown static obstacles, an environment with unknown dynamic obstacles, and an environment with a dynamic target. The proposed approach can solve a local minima problem in the environment with static obstacles. The online optimization method is performed using two phases which are the sensors’ reading phase and the path calculation phase and the results are given based on computer simulation in different unknown environments. A comparative study was conducted between the suggested algorithm and two other algorithms and the results showed that the AVOA algorithm was better in avoiding obstacles successfully including the local minima situation. Finally, the average enhancement rates in the path length compared with the Adaptive Particle Swarm Optimization (APSO) and the Hybrid Fuzzy-Wind Driven Optimization (WDO) are 2.21% and 1.02207%, respectively.
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Wang, Yankai, Qiaoling Du, Tianhe Zhang i Chengze Xue. "The WL_PCR: A Planning for Ground-to-Pole Transition of Wheeled-Legged Pole-Climbing Robots". Robotics 10, nr 3 (27.07.2021): 96. http://dx.doi.org/10.3390/robotics10030096.
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Hybrid mobile robots with two motion modes of a wheeled vehicle and truss structure with the ability to climb poles have significant flexibility. The motion planning of this kind of robot on a pole has been widely studied, but few studies have focused on the transition of the robot from the ground to the pole. In this study, a locomotion strategy of wheeled-legged pole-climbing robots (the WL_PCR) is proposed to solve the problem of ground-to-pole transition. By analyzing the force of static and dynamic process in the ground-to-pole transition, the condition of torque provided by the gripper and moving joint is proposed. The mathematical expression of Centre of Mass (CoM) of the wheeled-legged pole-climbing robots is utilized, and the conditions for the robot to smoothly transition from the ground to the vertical pole are proposed. Finally, the feasibility of this method is proved by the simulation and experimentation of a locomotion strategy on wheeled-legged pole-climbing robots.
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Hewawasam, Hasitha, Yousef Ibrahim i Gayan Kahandawa. "A Novel Optimistic Local Path Planner: Agoraphilic Navigation Algorithm in Dynamic Environment". Machines 10, nr 11 (16.11.2022): 1085. http://dx.doi.org/10.3390/machines10111085.
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This paper presents a novel local path planning algorithm developed based on the new free space attraction (Agoraphilic) concept. The proposed algorithm is capable of navigating robots in unknown static, as well as dynamically cluttered environments. Unlike the other navigation algorithms, the proposed algorithm takes the optimistic approach of the navigation problem. It does not look for problems to avoid, but rather for solutions to follow. This human-like decision-making behaviour distinguishes the new algorithm from all the other navigation algorithms. Furthermore, the new algorithm utilises newly developed tracking and prediction algorithms, to safely navigate mobile robots. This is further supported by a fuzzy logic controller designed to efficiently account for the inherent high uncertainties in the robot’s operational environment at a reduced computational cost. This paper also includes physical experimental results combined with bench-marking against other recent methods. The reported results verify the algorithm’s successful advantages in navigating robots in both static and dynamic environments.
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Parhi, D. R., i M. K. Singh. "Real-time navigational control of mobile robots using an artificial neural network". Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 223, nr 7 (24.03.2009): 1713–25. http://dx.doi.org/10.1243/09544062jmes1410.
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This article deals with the reactive control of an autonomous robot, which moves safely in a crowded real-world unknown environment and reaches a specified target by avoiding static as well as dynamic obstacles. The inputs to the proposed neural controller consist of left, right, and front obstacle distance to its locations and the target angle between a robot and a specified target acquired by an array of sensors. A four-layer neural network has been used to design and develop the neural controller to solve the path and time optimization problem of mobile robots, which deals with cognitive tasks such as learning, adaptation, generalization, and optimization. The back-propagation method is used to train the network. This article analyses the kinematical modelling of mobile robots as well as the design of control systems for the autonomous motion of the robot. Training of the neural net and control performances analysis were carried out in a real experimental set-up. The simulation results are compared with the experimental results and they show very good agreement.
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Tang, Swee Ho, Che Fai Yeong i Eileen Lee Ming Su. "Comparison between Normal Waveform and Modified Wavefront Path Planning Algorithm for Mobile Robot". Applied Mechanics and Materials 607 (lipiec 2014): 778–81. http://dx.doi.org/10.4028/www.scientific.net/amm.607.778.
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Mobile robot path planning is about finding a movement from one position to another without collision. The wavefront is typically used for path planning jobs and appreciated for its efficiency, but it needs full wave expansion which takes significant amount of time and process in large scale environment. This study compared wavefront algorithm and modified wavefront algorithm for mobile robots to move efficiently in a collision free grid based static environment. The algorithms are compared in regards to parameters such as execution time of the algorithm and planned path length which is carried out using Player/Stage simulation software. Results revealed that modified wavefront algorithm is a much better path planning algorithm compared to normal wavefront algorithm in static environment.
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Rafai, Anis Naema Atiyah, Noraziah Adzhar i Nor Izzati Jaini. "A Review on Path Planning and Obstacle Avoidance Algorithms for Autonomous Mobile Robots". Journal of Robotics 2022 (1.12.2022): 1–14. http://dx.doi.org/10.1155/2022/2538220.
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Mobile robots have been widely used in various sectors in the last decade. A mobile robot could autonomously navigate in any environment, both static and dynamic. As a result, researchers in the robotics field have offered a variety of techniques. This paper reviews the mobile robot navigation approaches and obstacle avoidance used so far in various environmental conditions to recognize the improvement of path planning strategists. Taking into consideration commonly used classical approaches such as Dijkstra algorithm (DA), artificial potential field (APF), probabilistic road map (PRM), cell decomposition (CD), and meta-heuristic techniques such as fuzzy logic (FL), neutral network (NN), particle swarm optimization (PSO), genetic algorithm (GA), cuckoo search algorithm (CSO), and artificial bee colony (ABC). Classical approaches have limitations of trapping in local minima, failure to handle uncertainty, and many more. On the other hand, it is observed that heuristic approaches can solve most real-world problems and perform well after some modification and hybridization with classical techniques. As a result, many methods have been established worldwide for the path planning strategy for mobile robots. The most often utilized approaches, on the other hand, are offered below for further study.
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Briskin, E. S., L. D. Smirnaya i K. S. Artemyev. "On the Control of Traction Characteristics and Resistance to Movement of Mobile Robots with Walking Propulsion Devices". Mekhatronika, Avtomatizatsiya, Upravlenie 24, nr 2 (6.02.2023): 101–6. http://dx.doi.org/10.17587/mau.24.101-106.
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The problem of increasing the traction and dynamic properties of mobile robots with walking propulsion devices is considered. The interdependence of the traction forces developed by the propulsion devices and the forces of resistance to the movement of robots, due to their interaction with the environment, is analyzed. A mathematical model is proposed based on the quasi-static nature of the robot’s movement and taking into account the static uncertainty of the problem. Static indeterminacy is due to the presence of propulsion devices on each of the sides and interacting with the supporting surface in the amount of more than two. A feature of the solution is also taking into account the gait and schedule of the robot’s movement, which characterize the time sequence of the propulsion devices being in the phase of interaction with the supporting surface and in the phase of transfer to a new position. The gait is also characterized by the mode coefficient, which is the ratio of the time the propulsion device is in the stance phase to the total time of the cycle of its movement. An optimality criterion is introduced on the basis of which the design perfection of the propulsion devices and the place of their installation on the robot is evaluated. The optimality criterion consists of two indicators: the value of the maximum traction force and the average force of resistance to movement. The tractive force is assumed to be proportional to the sum of the maximum normal loads acting on each propulsion device unit, and the resistance force to the squares of the same loads. Simulation modeling has been carried out, proving the dependence of the magnitude of traction properties and the forces of resistance to movement on the location of the propulsion devices. Two systems of vertical arrangement of the points of suspension of propulsion devices were compared. It has been established that a sufficiently small change in the vertical coordinate of the suspension point of even one propulsion devices has a noticeable change in the maximum traction forces and movement resistance forces. It is concluded that by adjusting the vertical position of the propulsion devices foot relative to the robot body, it is possible to control the traction properties and movement resistance, as well as the importance of the positioning accuracy of the foot of the propulsion devices walking mechanism during movement.
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Dorfling, Anchal, i C. E. van Daalen. "A motion segmentation technique for mobile robots using probabilistic models". MATEC Web of Conferences 370 (2022): 07004. http://dx.doi.org/10.1051/matecconf/202237007004.
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A dynamic environment can be challenging for a robot to navigate; it should avoid collisions with objects while determining its position in its environment (localisation). Thus, it is necessary for a mobile robot to take measurements of its environment, such as features from camera images, to determine whether objects are static or dynamic (motion segmentation). This is difficult to do as knowledge of static objects is required for localisation which is then used to track the trajectories of dynamic objects. This paper proposes a motion segmentation technique that classifies objects as static or dynamic by measuring the change in distance between them across many time steps; this removes the need for localisation information. The technique is adapted from a probabilistic method for outlier removal and existing motion segmentation techniques. A simple, 1D environment is simulated to show proof of concept. Additionally, a few strategies for PGM model construction are investigated where the results show a clear relationship between accuracy and computational times.
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Yinka-Banjo, Chika O., i Ukamaka Hope Agwogie. "Swarm Intelligence Optimization Techniques in Mobile Path Planning - A Review". International Journal of Engineering Research in Africa 37 (sierpień 2018): 62–71. http://dx.doi.org/10.4028/www.scientific.net/jera.37.62.
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In the present world, mobile robot has been widely used for many functions across different areas of life. These mobile robots can be engaged in a static or dynamic environment where they are expected to accomplish a task optimally against all odds. Path planning for mobile robot is a very crucial problem in robotics that has been greatly researched upon; it is aimed at finding an optimal path in a given environment from a start point to the goal point. Several techniques have been employed in solving this crucial problem. These techniques are broadly classified as classical and heuristics. The Swarm Intelligence Techniques form a sub-class of the heuristics approach. The aim of this research is to review the swarm intelligence techniques in solving the mobile robot path planning problem. The drawbacks and merits of each of the techniques were discussed and a comparative analysis was given.