Journal articles on the topic 'Maze Solving Robot'

<p>Swam Intelligence provides a basis with which it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. This paper presents design and implementation of swam robotics in a multi-agent environment. At the beginning, robot agents are ignorant of the maze. The robots are programmed with Flood fill algorithm to solve maze. The robot scans maze and stores the values in EEPROM. The robot agent shares the information to other robot agents through wireless communication. The proposed flood fill algorithm is found to be effective tool for solving maze of moderate size.</p>

The problem of micromouse is 30 years old but its importance in the field of robotics is unparalleled, as it requires a complete analysis & proper planning to solve the problem. This paper proposes two computationally efficient algorithms for maze solving. Most of the reported algorithms explore complete maze before finding the shortest path to the center of the maze, thereby taking large exploration time. Our proposed algorithms take less time in maze exploration by exploring the maze partially and by traversing less number of cells to reach the center of the maze. An optimal method for maze solving with partial exploration of the maze can hardly be found applicable to all type of mazes, but our algorithms are found to be efficient in most of the cases. Simulation of our proposed algorithms on the some standard mazes show that one of the two algorithms described in this paper gives the better solution by only partially exploring the maze and the other algorithm also gives the comparative results when compared with the algorithms reported in the literature.

This paper is about a robot that would be able to solve mazes or labyrinths and look for the exit. The project will utilize the PIC microcontroller. This is like those in the micromouse competitions since it resembles a mouse put in a labyrinth searching for its cheese. This would also implement the Wall Follower algorithm to solve the maze and will use proximity sensors to detect the walls of the labyrinth. The robot would be as small as possible as to make its navigation of the maze more efficient in terms of turning left or right, or even doing a full U-turn since a bulky robot would have a hard time navigating the turns in the maze. This project would also require an 8x8-tiled square maze to effectively apply the algorithm and to have a test labyrinth to work on.

The point of education in the early stage of studying robotics is understanding its basic principles joyfully. Therefore, this paper creates a simulation program of indoor navigations using an open-source code in Python to make navigation and control algorithms easier and more attractive to understand and develop. We propose the maze-solving-robot simulation as a teaching medium in class to help students imagine and connect the robot theory to its actual movement. The simulation code is built for free to learn, improve, and extend in robotics courses or assignments. A maze-solving robot study case is then done as an example of implementing navigation algorithms. Five algorithms are compared, such as Random Mouse, Wall Follower, Pledge, Tremaux, and Dead-End Filling. Each algorithm is simulated a hundred times in every type of the proposed mazes, namely mazes with dead ends, loops only, and both dead ends and loops. The observed indicators of the algorithms are the success rate of the robots reaching the finish lines and the number of steps taken. The simulation results show that each algorithm has different characteristics that should be considered before being chosen. The recommendation of when-to-use the algorithms is discussed in this paper as an example of the output simulation analysis for studying robotics.

Micromouse is a small autonomous electronic-mechanical robot, which is able to navigate through an unknown maze from the start to the destination. The main challenge for micromouse is to work out the maze after searching, find the optimum path for the shortest fast-run time and control the robot to win. Flood-fill algorithm is used in this project to develop a solver which is able to help the robot for finding the ‘best’ route from the starting position to the ‘goal’, maze solving result shows the correctness.

<p><em><span>Ruangan ibadah berjamaah adalah tempat yang sering digunakan banyak orang secara bersamaan dan menjadi tempat potensial guna penyebaran Corona.Virus yang di bawa oleh orang terinfeksi dapat menempel pada lantai , tembok kursi dan isi ruangan sehingga terhirup oleh jamaah saat melakukan ibadah, sehingga diperlukan alat guna membantu mensterilkan ruangan ibadah secara efisien. Dengan robot yang dilengkapi dengan sinar UVC diharapkan dapat membantu proses sterilisiasi secara efektif. Tujuan penelitian ini adalah guna menganalisa kinerja sistem robot sterilisasi dengan kendali Maze Solving, guna dapat bekerja dengan gerak lurus dan berputar. Pembaruan pada penelitian ini adalah penerapan kendali menggunakan algoritma Maze Solving pada robot sterilisasi ruangan. Penelitian ini dilakukan dengan tahap analisa, pengkodean, dan uji coba. Algoritma Maze Solving dengan KP=10, Ki=0 dan Kd=120 dengan kombinasi tambahan rotary encoder, sensor kompas dan sensor jarak. Hasil uji memperlihatkan peningkatan kerja robot dengan nilai standart deviasi tertinggi guna poin kelurusan gerak 10,48 menjadi 0,34 ketepatan jarak tempuh dari 10,4 menjadi 0,42 . Waktu yang dibutuhkan robot sterilisasi pada ruangan 10 m x 10 m adalah 54,5 menit dan pembacaan halangan rintang dengan sensor jarak akurat dibawah 60cm.</span></em></p>

Micromouse is a small autonomous robot, which must navigate itself through an unknown maze from the start to the destination.One of the main challenges for micromouse is to control its two motors, which are used to control micromouse’s motion in solving the maze. Detailed design of an improved PD controller is given,which has to update the velocity and acceleration values of the motors when it wants to control the robot. Motion profile generator and motion command execution routine is designed to output a smooth motion for the robots.

A line maze robot training course, which contains the hardware circuit implementation, firmware programming skills and the shortest path algorithm, is presented in this paper. The training course is used for vocation senior high school teachers and students. The major topic for students is to develop the proper firmware programming to achieve the better performance and students are encouraged to pass the small contest in the end of the workshop. The low-cost educational platform is easily by the economically disadvantaged students. Students, who join the workshop can learn the basic C language, the firmware programming skills for microcontrollers, the concept of the shortest path algorithm for line maze robot, just spend less $40 USD to buy the robots. The contributions of this training course are as follows: 1) studying the hardware implementation knowledge, 2) developing microcontroller-related firmware programming skills, 3) learning motion control skills of the line maze robot, and 4) learning line-maze solving algorithms. Few students, who join this training workshop and learn the related hardware, firmware and algorithm, can find the shortest path form source to target in the line map. The feedback of the most students shows that the training course gives them the motivation to actively learn the necessary practical skills to design the firmware programming to guide the line maze robot.

A long-term vision of evolutionary robotics is a technology enabling the evolution of entire autonomous robotic ecosystems that live and work for long periods in challenging and dynamic environments without the need for direct human oversight. Evolutionary robotics has been widely used due to its capability of creating unique robot designs in simulation. Recent work has shown that it is possible to autonomously construct evolved designs in the physical domain; however, this brings new challenges: the autonomous manufacture and assembly process introduces new constraints that are not apparent in simulation. To tackle this, we introduce a new method for producing a repertoire of diverse but manufacturable robots. This repertoire is used to seed an evolutionary loop that subsequently evolves robot designs and controllers capable of solving a maze-navigation task. We show that compared to random initialisation, seeding with a diverse and manufacturable population speeds up convergence and on some tasks, increases performance, while maintaining manufacturability.

Discrete mathematics covers the field of graph theory, which solves various problems in graphs using algorithms, such as coloring graphs. Part of graph theory is focused on algorithms that solve the passage through mazes and labyrinths. This paper presents a study conducted as part of a university course focused on graph theory. The course addressed the problem of high student failure in the mazes and labyrinths chapter. Students’ theoretical knowledge and practical skills in solving algorithms in the maze were low. Therefore, the use of educational robots and their involvement in the teaching of subjects in part focused on mazes and labyrinths. This study shows an easy passage through the individual areas of teaching the science, technology, engineering, and mathematics (STEM) concept. In this article, we describe the research survey and focus on the description and examples of teaching in a university course. Part of the work is the introduction of an easy transition from the theoretical solution of algorithms to their practical implementation on a real autonomous robot. The theoretical part of the course introduced the issues of graph theory and basic algorithms for solving the passage through the labyrinth. The contribution of this study is a change in the approach to teaching graph theory and a greater interconnection of individual areas of STEM to achieve better learning outcomes for science students.

Abstract This paper discusses structuring of hardware and software for an autonomous social robot. It shows that the real-world social robot operations face the challenge of environmental variability and uncertainty of the objective parameters. Thus, a social robot must be capable of situation analysis for better autonomy. We propose a modular distributed structure of the control system. Separate modules monitor the status and control the subsystems of the robot. General coordination of subsystems is provided by the Supervisor module. For the robot to function autonomously, the Supervisor must be capable of situation analysis and its key functions: objective retrieval and analysis, situation description, configuring and strategizing the solution. The robot’s sensory inputs help acquire the objective and its parameters to describe the situation. Description relies on the database of a priori knowledge of the environment and its objects. Analysis is linked to a reduction in the uncertainty of the objective parameters and situation description. For a case study, the paper demonstrates a maze-solving strategy as affected by the situation.

Multi-robot path planning is abstracted as the problem of computing a set of non-colliding paths on a graph for multiple robots. A naive search of the composite search space, although complete, has exponential complexity and becomes computationally prohibitive for problems with just a few robots. This work proposes an efficient and complete algorithm for solving a general class of multi-robot path planning problems, specifically those where there are at most n-2 robots in a connected graph of n vertices. The algorithm employs two primitives: a "push" operation where a robot moves toward its goal until no further progress can be made, and a "swap" operation that allows two robots to swap positions without altering the configuration of any other robot. Simulated experiments compare the proposed approach with several other centralized and decoupled planners, and show that the proposed technique has highly competitive computation time and easily scales to problems involving 100s of robots, solving them in under 5 seconds.

This paper defines the research area of Diversity-enhanced Autonomy in Robot Teams (DART), a novel paradigm for the creation and design of policies for multi-robot coordination. Although current approaches to multi-robot coordination have been successful in structured, well-understood environments, they have not been successful in unstructured, uncertain environments, such as disaster response. Although robot hardware has advanced significantly in the past decade, the way we solve multi-robot problems has not. Even with significant advances in the field of multi-robot systems, the same problem-solving paradigm has remained: assumptions are made to simplify the problem, and a solution is optimized for those assumptions and deployed to the entire team. This results in brittle solutions that prove incapable if the original assumptions are invalidated. This paper introduces a new multi-robot problem-solving paradigm which uses a diverse set of control policies that work together synergistically within the same team of robots. Such an approach will make multi-robot systems more robust in unstructured and uncertain environments, such as in disaster response, environmental monitoring, and military applications, and allow multi-robot systems to extend beyond the highly structured and highly controlled environments where they are successful today.

Manufacturing Environment Production of one or more products Dedicated production lines to do or areas. Convenience stores stock items that can manufacture or have them made to order, only if requested by the buyer. The objective of this thesis Finding the best cleaning location Manufacturing Environment or Gray Relational Analysis (GRA) method showing. GRA (Gray Relational Analysis) Method, Cincinnati Milagron T3-726, Cybotech V15 Electric Robot, Hitachi America Process Robot, Unimation PUMA 500/600, United States Robots Maker 110 Alternatives or Load Capacity, Computational Steps for Solving Repeatable Multi-Attribute Decision-Making Problems Node Speed, Memory Capacity, the evaluation parameters reached by the handler The United States Robots Maker 110is got the first rank whereas the Hitachi America Process Robot is having the lowest rank. In this paper Manufacturing Environment United States Robots Maker 110is got the first rank whereas the Hitachi America Process Robot is having the lowest rank

In this paper, we propose a method to assess the collision risk and a strategy to avoid the collision for solving the problem of dynamic real-time collision avoidance between robots when a multi-robot system is applied to perform a given task collaboratively and cooperatively. The collision risk assessment method is based on the moving direction and position of robots, and the collision avoidance strategy is based on the artificial potential field (APF) and the fuzzy inference system (FIS). The traditional artificial potential field (TAPF) has the problem of the local minimum, which will be optimized by improving the repulsive field function. To adjust the speed of the robot adaptively and improve the security performance of the system, the FIS is used to plan the speed of robots. The hybridization of the improved artificial potential field (IAPF) and the FIS will make each robot safely and quickly find a collision-free path from the starting position to the target position in a completely unknown environment. The simulation results show that the strategy is effective and useful for collision avoidance in multi-robot systems.

The presence of collaborative robots in industrial environments requires that their control strategies include collision avoidance in the generation of trajectories. In general, collision avoidance is performed via additional displacements of the kinematic chain that make the robot move far from the objects that are occasionally inserted into its safety workspace. The variability of the coordinates of the collision points inside the safety volume leads to abrupt movements for the robot. This paper presents a general method for smoothing abrupt movements in robots with one degree of redundancy for collision-avoidance trajectories, employing a second-order digital filter designed with adjustable critical damping. The method is illustrated by applying it to a redundant robot with a spherical–revolute–spherical type (SRS-type) kinematic chain, which is a benchmark used to test the algorithms ideated for solving this problem. This paper also presents an alternative algorithm for the inverse kinematics of the SRS-type robot and the computational experiments that show the collision avoidance proposal’s performance and its properties through graphical results.

Automated model generation and solution for motion planning and re-planning of robotic systems will play an important role in the future reconfigurable manufacturing systems. Solving the inverse kinematic problem has always been the key issue for computer-controlled robots. Considering the large amount of similarities that exist among the industrial 6R robotic systems, this work classifies them into two main types (Puma-type and Fanuc-type) and then provides a unified geometric solution based on a unified kinematic structure called Generic Puma-Fanuc (GPF) model. A widespread study of different kinematic groups originating from eleven robot manufacturers made it possible to develop the GPF model that can be reconfigured according to the D-H rules (Denavit, and Hartenberg1). A graphical interface by which the robot kinematic model is represented and the D-H parameters are auto-generated for use in solving the inverse kinematic problem. A generic solution module called Unified Kinematic Modeler and Solver (UKMS) implements the geometric approach for solving the inverse kinematic problem. The outcomes are then employed for robot control. Numerical examples are presented for exploring the solution capabilities of our unified approach.

Trajectory tracking for autonomous vehicles is usually solved by designing control laws that make the vehicles track predetermined feasible trajectories based on the trajectory error. This type of approach suffers from the drawback that usually the vehicle dynamics exhibits complex nonlinear terms and significant uncertainties. Toward solving this problem, this work proposes a novel approach in trajectory tracking control for nonholonomic mobile robots. We use a nonlinear model predictive controller to track a given trajectory. The novelty is introduced by using a set of modifications in the robot model, cost function, and optimizer aiming to minimize the steady-state error rapidly. Results of simulations and experiments with real robots are presented and discussed verifying and validating the applicability of the proposed approach in nonholonomic mobile robots.

Abstract. This paper presents a novel method to make denim-fabric-polishing robots perform their primary task flexibly and efficiently within a limited workspace. Link lengths are optimized based on an adaptive fireworks algorithm to improve the comprehensive dexterity index. A forward kinematics analysis of the denim-fabric-polishing robot is conducted via the D–H method; the workspace is analyzed according to the needs at hand to determine the range of motion of each joint. To solve the movement condition number of the Jacobian matrix, the concept of low-condition-number probability is established, and a comprehensive dexterity indicator is constructed. The influence of the robot's size on the condition number and comprehensive dexterity index is determined. Finally, the adaptive fireworks algorithm is used to establish the objective optimization function by integrating the dexterity index and other performance indicators. The optimization results show that when the comprehensive dexterity index is taken as the optimization objective, the dexterity comprehensive index and other performance indices of the robot are the lowest; that is, the robot is more flexible. Compared with the traditional genetic algorithm and particle swarm algorithm, the adaptive fireworks algorithm proposed in this paper has better solving speed and solving precision. The optimized workspace of the robot meets the requirements of the polishing task. The design also yields a sufficiently flexible, efficient, and effective robot.

This study is devoted to the challenges of motion planning for mobile robots with smart machine vision systems. Motion planning for mobile robots in the environment with obstacles is a problem to deal with when creating robots suitable for operation in real-world conditions. The solutions found today are predominantly private, and are highly specialized, which prevents judging of how successful they are in solving the problem of effective motion planning. Solutions with a narrow application field already exist and are being already developed for a long time, however, no major breakthrough has been observed yet. Only a systematic improvement in the characteristics of such systems can be noted. The purpose of this study: develop and investigate a motion planning algorithm for a mobile robot with a smart machine vision system. The research subject for this article is a motion planning algorithm for a mobile robot with a smart machine vision system. This study provides a review of domestic and foreign mobile robots that solve the motion planning problem in a known environment with unknown obstacles. The following navigation methods are considered for mobile robots: local, global, individual. In the course of work and research, a mobile robot prototype has been built, capable of recognizing obstacles of regular geometric shapes, as well as plan and correct the movement path. Environment objects are identified and classified as obstacles by means of digital image processing methods and algorithms. Distance to the obstacle and relative angle are calculated by photogrammetry methods, image quality is improved by linear contrast enhancement and optimal linear filtering using the Wiener-Hopf equation. Virtual tools, related to mobile robot motion algorithm testing, have been reviewed, which led us to selecting Webots software package for prototype testing. Testing results allowed us to make the following conclusions. The mobile robot has successfully identified the obstacle, planned a path in accordance with the obstacle avoidance algorithm, and continued moving to the destination. Conclusions have been drawn regarding the concluded research.

The known algorithms for planning the trajectory of movement of mobile robots in an unknown environment have high computational complexity or do not allow finding the trajectory that is optimal along the length of the path, while maintaining a safe distance from obstacles. The aim of the work is to increase the efficiency of solving the problem of planning the trajectory of movement of mobile robots from the initial position to the final position in an unknown environment with obstacles, taking into account the limited capabilities (sensory and computational) of mobile robots. The solution to this problem was carried out on the basis of step-by-step optimization of the current position of the robot relative to a given target. The proposed method analyzes the possibility of a robot moving in directions determined by means of analytical geometry based on measurements of on-board distance sensors. An element of scientific novelty is the procedure for calculating trajectory segments based on the choice of an intermediate state and correcting the trajectory taking into account the measurements of the on-board distance sensors of the mobile robot. The proposed method makes it possible to search for the trajectory of a mobile robot in an unknown environment while ensuring a given distance to obstacles. The use of the presented algorithm allows the robot to maintain a high efficiency of the task while functioning in conditions of information deficiency. The reliability of the results was confirmed in the course of software simulation. The solution of the problem, taking into account these features, made it possible to reduce the computational complexity of the method, as well as to remove restrictions on the use of trajectory planning algorithms for mobile robots with low-performance on-board sensors and computing devices. The presented algorithm is implemented in the form of software in the Python programming language, which can be used to simulate autonomous control systems for mobile robots.

It is well known that robots are being skillfully applied and with favorable performance in a variety of fields, for use in the Japanese manufacturing industry in particular, thanks to progress in robot technology. Today, robots are expected to accommodate men and in the near future be utilized in the field of home life in compliance with human beings. Pessimistically speaking, however, it is impossible to deny that conventional robots, such as teaching playback robots (which men must operate directly), are not able to play roles in the future as expected, so that the development of a new control system which is able to overcome conventional systems in performance ability is indispensable. In other words, flexible control systems by which robots are able to behave autonomously, with minimum human interference is urgently required. We believe that the following three concepts are indispensable for a robot to be equipped with flexibility. a) Manipulators/hands and lggs / wheek with human flexibility. b) Control of flexible and intelligent motions for control in manipulation/handling and locomotion; c) Flexible intelligence and a sense of judgement which permits the robot to execute motions autonomously, adapting itself to the requirements of the human environment. Solving these problems will require investigation into information processing, a study into the function of the brain and central nervous system of human and other living bodies. Thus the information processing theory about neural networks which simulate the functions of the brain has progressed rapidly to activate R & D on the application of motion control and speech processing which have made use of the conventional Neumann computer difficult to handle. Neural networks have the capacity of parallel distributed processing and self-organization as well as learning capacity. Its theory has provided an effective basis for materialization of flexible robots. In the field of level b. and c. mentioned earlier, the neural network theory comprises a large potential to be applied to robots, so that attention is being focused on it. Nevertheless, information processing by neural network is not omnipotent for solving such problems. Presently, it is difficult for a neural network to solve problems which require complex calculations in robot control; for instance, such controls that take force and acceleration into account. Control of flexible robots which mobilize whole arms will require parallel processing of data obtained from many sensors and to control numerous degrees of motion. Therefore, it has become increasingly important for problem solving to combine such problems inherent to robots with parallel processing, self-organization and learning ability of neural networks. From this point of view, therefore, further promotion of R & D on the application technology of neural network for robots is important. These efforts will produce a new neural network-theory for robots and eventually permit autonomous motion. This special issue compilied articles related to applications of neural network to robots, which were produced in the above mentioned environment, from a review on neuromorfhic control, through dynamic system control, optimal trajectory, planning of motion for handling, manipulator locomotion and travelling, to problems in application systems. We hope these articles help our readers understand the present state of Japanese R & D and the application of neural network for robots, as well as new subjects possible for progress in the future. Finally, we gratefully acknowledge Prof. Toshio Fukuda (who contributed a review) and other contributors on their latest achievements.

This article presents the methods that allow forming quantitative estimations of functional characteristics of a group of autonomous mobile robots (AMRs) and local areas of the environment surrounding it. The evaluation of the environment is based on the analysis of scattering of the cloud of obstacle points and made using the information formed by the computer vision system (CVS), which every robot in the group has. The core element of CSV is 3D lidar. Quantitative data about the complexity of the environment can be used for determining the optimal methods of solving the planning tasks and forming the patterns of group formation. Such data about the complexity of local areas of the environment can also be used for determining them as insurmountable for a single robot or a group of robots. The reason for such a decision can be the violation of safety rules and breaking of the group formation. The assessment of robots’ functional characteristics is performed based on the fuzzy model that consists of separate fuzzy classifiers; each of them allows obtaining a quantitative estimation of one of the parameters. The hierarchic structure of the used fuzzy model makes it significantly easier to synthesize and analyze it.

Problem solving skills are very important in supporting social development. Children with problem solving skills can build healthy relationships with their friends, understand the emotions of those around them, and see events with other people's perspectives. The purpose of this study was to determine the implementation of playing unplugged coding programs in improving early childhood problem solving skills. This study used a classroom action research design, using the Kemmis and Taggart cycle models. The subjects of this study were children aged 5-6 years in Shafa Marwah Kindergarten. Research can achieve the target results of increasing children's problem-solving abilities after going through two cycles. In the first cycle, the child's initial problem-solving skills was 67.5% and in the second cycle it increased to 80.5%. The initial skills of children's problem-solving increases because children tend to be enthusiastic and excited about the various play activities prepared by the teacher. The stimulation and motivation of the teacher enables children to find solutions to problems faced when carrying out play activities. So, it can be concluded that learning unplugged coding is an activity that can attract children's interest and become a solution to bring up children's initial problem-solving abilities. Keywords: Early Childhood, Unplugged Coding, Problem solving skills References: Akyol-Altun, C. (2018). Algorithm and coding education in pre-school teaching program integration the efectiveness of problem-solving skills in students. Angeli, C., Smith, J., Zagami, J., Cox, M., Webb, M., Fluck, A., & Voogt, J. (2016). A K-6 Computational Thinking Curriculum Framework: Implications for Teacher Knowledge. Educational Technology & Society, 12. Anlıak, Ş., & Dinçer, Ç. (2005). 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Purpose The purpose of this paper is to present a follow-the-leader motion strategy for multi-section continuum robots, which aims to make the robot have the motion ability in a confined environment and avoid a collision. Design/methodology/approach First, the mechanical design of a multi-section continuum robot is introduced and the forward kinematic model is built. After that, the follow-the-leader motion strategy is proposed and the differential evolution (DE) algorithm for calculating optimal posture parameters is presented. Then simulations and experiments are carried out on a series of predefined paths to analyze the performance of the follow-the-leader motion. Findings The follow-the-leader motion can be well performed on the continuum robots this study proposes in this research. The experimental results show that the deviation from the path is less than 9.7% and the tip error is no more than 15.6%. Research limitations/implications Currently, the follow-the-leader motion is affected by the following factors such as gravity and continuum robot design. Furthermore, the position error is not compensated under open-loop control. In future work, this paper will improve the accuracy of the robot and introduce a closed-loop control strategy to improve the motion accuracy. Originality/value The main contribution of this paper is to present an algorithm to generate follow-the-leader motion of the continuum robot based on DE. This method is suitable for solving new arrangements in the process of following a nonlinear path. Then, it is expected to promote the engineering application of the continuum robot.

Abstract In this article, we aim to evaluate the role of robots’ personality-driven behavioural patterns on users’ intention to use in an entertainment scenario. Toward such a goal, we designed two personalities: one introverted with an empathic and self-comparative interaction style, and the other extroverted with a provocative and other-comparative interaction style. To evaluate the proposed technology acceptance model, we conducted an experiment (N = 209) at a public venue where users were requested to play a game with the support of the TIAGo robot. Our findings show that the robot personality affects the acceptance model and three relevant drivers: perceived enjoyment, perceived usefulness, and social influence. The extroverted robot was perceived as more useful than the introverted, and participants who interacted with it were faster at solving the game. On the other hand, the introverted robot was perceived as more enjoyable but less useful than the extroverted, and participants who interacted with it made fewer mistakes. Taken together, these findings support the importance of designing proper robot personalities in influencing users’ acceptance, featuring that a given style can elicit a different driver of acceptance.

Abstract. Among parallel robots, spherical robots occupy an important place. Most applications of spherical manipulators can be found in orienting devices, such as camera orienting and medical instrument alignment. A spherical parallel robot is, in general, made up of the base platform and the moving platform. This mobile platform and base are connected by three equally spaced legs, each consisting of revolute joints only. The axes of all joints intersect at a common point, which is called the center of rotation. The motion of the moving platform is confined on the surface of a sphere centered at the rotation center. A spherical parallel robot provides 3 degrees of freedom of pure rotations. These robots have been the subject of many papers dealing with the structure, the problems of position and velocity, workspace modeling, singularity analysis, and some problems with the dynamic analysis. However, not all the important problems have been solved. These concern the problem of accuracy. This paper presents accuracy of the spherical parallel. In the considered spherical manipulator, each leg consists of five kinematic pairs. The kinematic accuracy is determined on the kinematic problem. The dynamic accuracy is estimated on the equation of motion. Examples of solving the problem of determining the positioning error of the output level are presented.

The research interest in the use robotics for education purposes has increased greatly in the last few years. However, no much consideration has been made to the benefits that the robots have in delivering content in STEM education. Educational robots have been used to support learning of STEM subjects but in the informal learning environment at different levels of education. This review assesses benefits of use of educational robots in teaching of these subjects to learners’ attitude towards the subjects and problem solving skills. In this research 25 papers were selected for the purpose of review through a process of search and review. The papers selected were analyzed based on similarity in their findings and mainly on the benefits educational robot activities towards teaching and learning of STEM subjects. The review reveals that robotic activities employed in education play an important role in enhancing STEM interest and also promoting problem solving skills. These benefits are greater to primary school learners than primary school learners and are realized greatly when the duration of experiment is not extended for longer durations. From the review it was noted that the robots have a greater impact in boys than in girls. The robots being multidisciplinary in nature can be utilized in teaching various subjects at different levels of education. The conclusions of this review will be useful as reference for future research in this field of study.

Applying the learning mechanism of natural living beings to endow intelligent robots with humanoid perception and decision-making wisdom becomes an important force to promote the revolution of science and technology in robot domains. Advances in reinforcement learning (RL) over the past decades have led robotics to be highly automated and intelligent, which ensures safety operation instead of manual work and implementation of more intelligence for many challenging tasks. As an important branch of machine learning, RL can realize sequential decision-making under uncertainties through end-to-end learning and has made a series of significant breakthroughs in robot applications. In this review article, we cover RL algorithms from theoretical background to advanced learning policies in different domains, which accelerate to solving practical problems in robotics. The challenges, open issues, and our thoughts on future research directions of RL are also presented to discover new research areas with the objective to motivate new interest.

The problem of controlling a group of special robots for application in the high-risk conditions (for example, for fire extinguishing, search for hazardous substances, or elimination of consequences of emergencies) is solved. According to the task, robots operate in the industrial and urban environment, i.e., the movement of robots is planar. Various strategies of group interaction between robots are analyzed; a literature review is conducted. Due to the task specifics, a decentralized management strategy has been selected. For solving the problem, a movement algorithm of a group of mobile robots with a subsequent visual check of the resulting algorithm operation is proposed. Implementation of the algorithm’s work is performed in the MATLAB environment. For preliminary algorithm verification and modeling of various dangerous cases, a model of robot group using the Mobile Robotics Simulation Toolbox of MATLAB was made. For a more detailed and accurate analysis of the real robot’s behavior, a model in the ROS package has been developed. That model interacts with the developed algorithm through the ROS Toolbox package of MATLAB. This software can be used for the training of engineering staff in the field of mathematical modeling, group control, and multi-agent systems. As a result of verification, the program and the model successfully solve the task. Yet, the model in the ROS package requires greater computational power because of the large number of complex calculations.

Due to motion constraint of 4-R(2-SS) parallel robot, it is difficult to calculate the translation component of hand–eye calibration based on the existing model solving method accurately. Additionally, the camera calibration error, robot motion error, and invalid calibration motion poses make it difficult to achieve fast and accurate online hand–eye calibration. Therefore, we propose a hand–eye calibration method with motion error compensation and vertical-component correction for 4-R(2-SS) parallel robot by improving the existing eye-to-hand model and solving method. Firstly, the eye-to-hand model of single camera is improved and the robot motion error in the improved model is compensated to reduce the influence of camera calibration error and robot motion error on model accuracy. Secondly, the vertical-component of hand–eye calibration is corrected based on vertical constraint between calibration plate and end effector in parallel robot to calculate the pose and motion error in calibration of 4-R(2-SS) parallel robot accurately. Thirdly, the nontrivial solution constraint of eye-to-hand model is constructed and adopted to remove invalid calibration motion poses and plan calibration motion. Finally, the proposed method was verified by experiments with a fruit sorting system based on 4-R(2-SS) parallel robot. Compared with random motion, the existing model, and solving method, the average time of online calibration based on planned motion decreases by 29.773 s and the average error of calibration based on the improved model and solving method decreases by 151.293. The proposed method can improve the accuracy and efficiency of hand–eye calibration of 4-R(2-SS) parallel robot effectively and further realize accurate and fast grasping.

Urgency of the research. Interest in this subject is aroused because, in the available sources, this kinematic structure is the least documented, even though it is required in certain applications (fast assembly of small parts,...). Target setting. The main goal was to design a workplace with a Scara robot. This workplace is used by the student to verify their theoretical knowledge gained from lectures in practice. They can try programming the robot, but also work with the camera system. Actual scientific researches and issues analysis. In 1961, (USA) the first industrial robot Unimate was put into the industrial practise for General Motors for welding of vehicle body. Since this industrial robot deployment has gone on for many years and many changes have been made in the field of industrial robotics in terms of mechanical properties and industrial robot control systems, taking account the requirements of applications in technical practise. Uninvestigated parts of general matters defining. This article focuses on analysis of the proposed of workplace with robot of kinematic structure Scara and parts of workplace. The research objective. The aim of the research was to design and assembly workplace with robot Scara with camera system by Omron. The statement of basic materials. The analysis consists of basic information about kinematic structure of Scara robots. Based on this knowledge the 3D model of workplace and parts is described. Conclusions. The robot workplace with the Scara robot and the Omron F150 camera system is designed for students to verify the theoretical knowledge gained from the lectures in practice. At the same time, the workplace can be used to solve and verify the knowledge in solving various projects related to the use of CCTV systems in a robotic workplace. Due to longterm use of the workplace in the educational process, where students were able to intervene in software and hardware equipment, several parts of the workplace were damaged. The next step is to upgrade the entire workplace.

In this paper, a dynamic analysis for a 5 degree of freedom (DOF) robotic arm with serial topology is presented. The dynamic model of the robot is based on importing a tri-dimensional CAD model of the robot into Simulink®-Simscape™-Multibody™. The dynamic model of the robot in Simscape is a necessary and important step in development of the mechanical structure of the robot. The correct choice of the electric motors is made according to the resistant joint torques determined by running the dynamic analysis. One can import complete CAD assemblies, including all masses, inertias, joints, constraints, and tri-dimensional geometries, into the model block. The first step for executing a dynamic analysis is to resolve the Inverse Kinematics (IK) problem for the redundant robot. The proposed method for solving the inverse kinematic problem for this type of structure is based on a geometric approach and validated afterwards using SimScape Multibody. Solving the inverse kinematics problem is a mandatory step in the dynamic analysis of the robot, this is required to drive the robot on certain user-imposed trajectories. The dynamic model of the serial robot is necessary for the simulation of motion, analysis of the robot’s structure and design of optimal control algorithms.

This paper presents a new method for solving the inverse kinematics of robot manipulators symbolically using computer algebra. The kinematics equations, including the trigonometric functions of joint displacements, are expressed as multivariate polynomial equations by transforming these functions into variables. The multivariate polynomial equations can be solved by evaluating their reduced Grobner basis. The properties for efficient evaluation of the reduced Grobner basis and the inverse kinematics of a robot, whose last three joint axes intersect at a point, are shown. This procedure is implemented using Maple V and built into ROSAM (Robot Symbolic Analysis, by Maple) that is a robot analysis library made by our group. An analysis example of a structurechanged PUMA type robot is given.

Based on affine transformation image kinematics and recurrence relations, the sub-region KLT feature extract with was designed and rules were given. Optimization of sum of absolute difference was used to match feature points. Diamond search template was adapted to make matching fast, and adaptive varying template size scheme was proposed to solve the problem the minimum SAD is not exclusive, and detailed procedure were described. In order to ensure that extracted feature points are on background, not on moving robot, adaptive iterative scheme was proposed and algorithm was designed. Through solving over-determined image kinematics equations using the least squares algorithm, got the motion parameters. According to the self-developed jitter compensation model, unintended motion was reduced by Kalman filter. Then use filtered parameters to reconstruct image. Based on two autonomous robots, experiment was completed. Results show method proposed meet requirements of accuracy and real time.

By absorbing the advantages of the rotary-driven Delta robot and linear-driven Delta robot, a Delta robot for pick-and-place operation that forms a crank-slider at the drive joint is designed.To take the most common gate shaped curve in Cartesian space as the motion trail of robotic pick-and-place operation, according to the kinematics inverse solution theory of Delta robot, this thesis mainly solves the output angular velocity of robot-driven joint. Establishing the static transfer mathematical model and solving the forced condition of driving joint. The simulation analysis show that after the upper slider-crank mechanism is connected to the driving joint, the angular velocity of the driving joint changes suddenly, which caused a rigid impact on the robot in the picking and releasing operation, though the force of the driving joint can be made smaller.

We present a constrained optimization method for multi-robot formation control in dynamic environments, where the robots adjust the parameters of the formation, such as size and three-dimensional orientation, to avoid collisions with static and moving obstacles, and to make progress towards their goal. We describe two variants of the algorithm, one for local motion planning and one for global path planning. The local planner first computes a large obstacle-free convex region in a neighborhood of the robots, embedded in position-time space. Then, the parameters of the formation are optimized therein by solving a constrained optimization, via sequential convex programming. The robots navigate towards the optimized formation with individual controllers that account for their dynamics. The idea is extended to global path planning by sampling convex regions in free position space and connecting them if a transition in formation is possible - computed via the constrained optimization. The path of lowest cost to the goal is then found via graph search. The method applies to ground and aerial vehicles navigating in two- and three-dimensional environments among static and dynamic obstacles, allows for reconfiguration, and is efficient and scalable with the number of robots. In particular, we consider two applications, a team of aerial vehicles navigating in formation, and a small team of mobile manipulators that collaboratively carry an object. The approach is verified in experiments with a team of three mobile manipulators and in simulations with a team of up to sixteen Micro Air Vehicles (quadrotors).

One of the problems in the development of multi-robotic systems is the safe navigation of a group of robots. To solve it, the restrictions imposed by the structural elements of its agents are determined. The article presents a multi-robotic system consisting of parallel and serial robots installed on mobile platforms. The parallel robot is made based on a tripod with the ability to rotate the robot’s base relative to the horizontal axis. The analysis of its working and technological area is carried out, taking into account singularity zones. The developed algorithms for determining the workspaces are based on deterministic methods for approximating the set of solutions to systems of nonlinear inequalities. In this case, restrictions in spaces of different coordinates are presented in the form of n-dimensional boxes. Approaches to solving two problems are proposed to determine the possible intersection of links for the collaborative performance of tasks by a multi-robotic system. The first task is to determine the intersection of the links for the given positions and the relative position of the manipulators. The second is in determining the minimum distance between the technological areas of manipulators, which consist of the workspace and all possible positions of the intermediate links.

To improve the automation, welding efficiency, and welding quality of duckbill welding of the cotton seeder, this study designed a cotton seeder duckbill welding robot. According to the characteristics of the duckbill weldment and welding requirements, the overall structure of the welding robot was determined, including the girdle feeding mechanism, static duckbill feeding mechanism, hinge feeding mechanism, welding fixture, welding actuator, and control system. To realize the continuous automatic feeding, positioning, fixing, welding, and unloading of the workpiece in the duckbill welding, the feeding mechanism adopts the method of cooperative cooperation of inductive proximity switch, electromagnet, and cylinder. The main body of the welding fixture adopts the pneumatic clamping method; the welding actuator adopts the synchronous belt module electric drive so that the welding torch can move in a straight line along the X axis and the Z axis. The welding process of the duckbill was simulated by Simufact Welding software, and the deformation and stress changes of the weldment were compared and analyzed when the single-sided single welding, the bilateral symmetrical double welding torch, two welding forms, and two welding process parameters were used to determine the welding process parameters of the welding robot. The prototype was made and the welding test was carried out. The test results show that the duckbill welding robot of the cotton seeder has stable feeding, solid clamping, accurate positioning, and high welding efficiency. According to the national standard, the appearance of the duckbill weld is inspected. The surface of the duckbill weld and the heat-affected zone has no cracks, incomplete fusion, slag inclusion, crater, and porosity. The forming quality of the welded parts is good. The design of the duckbill welding robot for cotton seeder is helpful in solving the problems of cumbersome positioning and clamping and low efficiency in manual and semi-automatic duckbill welding robots, which provides a strong guarantee for the large-scale and standardized welding production of the dibbler duckbill.

Abstract This article is focused on enhancement of HW/SW device by cooperation with a smartphone interface. The device was a programmable Lego Mindstorms Education EV3 set in the form of a robot designed to solve the Rubik’s Cube. The aim of the research was to replace the built-in color sensor with a camera that would allow the cube scanning process to be accelerated. Two approaches were chosen to meet the goal: the NXTcam camera, accessible as an accessory to expand the set, and the camera built into the smartphone. The use of NXTcam led to better scan time, but this result was prone to external influences. The camera on the smartphone sped up the scanning process to 57% of the original time. The impact of external factors on the outcome was significantly lower, compared to NXTcam. In the experiment, the cube solving process was observed in natural light, with addition distractive light source and in artificial light.

Currently, the path planning problem is one of the most researched topics in autonomous robotics. That is why finding a safe path in a cluttered environment for a mobile robot is an important requirement for the success of any such mobile robot project. In this work, a developed algorithm based on free segments and a turning point strategy for solving the problem of robot path planning in a static environment is presented. The aim of the turning point approach is to search a safe path for the mobile robot, to make the robot moving from a starting position to a destination position without hitting obstacles. This proposed algorithm handles two different objectives which are the path safety and the path length. In addition, a robust control law which is called sliding mode control is proposed to control the stabilization of an autonomous mobile robot to track a desired trajectory. Finally, simulation results show that the developed approach is a good alternative to obtain the adequate path and demonstrate the efficiency of the proposed control law for robust tracking of the mobile robot.

Abstract In view of the problems of manual pruning, such as time-consuming, labor-intensive, low efficiency and low degree of automation, the structure and working principle of the robot for tree-climbing and pruning were studied. Finding the problems in the process of product design, analyzing and defining them, transforming them into the standard mode of solving problems, and using TRIZ theory according to the essence of contradictions to solve the contradictions one by one. The virtual prototype was created to carry out the interference analysis and kinematics simulation analysis of the whole machine. The robot for tree-climbing and pruning was designed by modular design method, which can automatically climb to a certain height to realize the function of pruning and cutting the top of the tree trunk. The duty cycle of the motor output is gradually adjusted by PID algorithm to make multiple motors work synchronously and keep the robot stable in the up-tree pruning process and down-tree process. The robot was made and tested. The experimental results show that the diameter of climbing trunk is 100 mm∼300 mm, and the climbing speed is 1 m/min. It can be used for tree-climbing, pruning lateral branches and cutting main trunks of high-straight trunk trees. It can be self-adaptively held, fall-resistant, obstacle-crossing, and manual operate to improve efficiency.

There are successful cases in lean manual assembly lines; however, in some cases, such as the ease of assembly in quicker cycle time, the designs are not satisfactory and must be transformed to semi-automation. This research studies human-robot task allocation when designing for semi-automation considering not only time-cost effectiveness as in the existing research but also assembly difficulty and ergonomic issues. A proposed methodology optimally determines what tasks should be performed by humans or robots, at which station, and in what sequence. A multi-objective linear programming (MOLP) model is proposed to simultaneously minimize total operating cost, cycle time, and ergonomic difficulty. Solving the model has two approaches: with and without optimal weights. The methodology is applied to a Lego-car assembly line. To illustrate the benefits of the proposed MOLP, a comparison between it and three single-objective models is made. Results show that the optimal-weight MOLP yields a better performance (a shorter cycle time, a lower cost, and especially, a significant ergonomic improvement) when compared to the other MOLP and single-objective models.

School students are a group that is very vulnerable to the risk of earthquake disasters in schools. Hence, a clearer understanding of the concept of earthquakes and readiness for earthquakes is a key element that needs to be given special attention by teachers in educating students. This scenario has prompted various studies to be conducted to evaluate and identify methods and strategies to improve understanding of concepts and earthquake preparedness to students. This is to help reduce risk and build disaster resilience among students. Therefore, the integration of the use of robots in the game learning module is able to help students in understanding the important concepts of earthquakes and the readiness that need to be taken when facing this disaster. This is due to the potential of the inclusion of robots in the teaching and learning process of games to boost student intrinsic motivation, enhance their critical thinking, problem-solving, and metacognition skills, and make it simpler for them to understand difficult concepts. To ensure that the teaching and learning process of the robot game module is perfectly implemented and meets the learning objectives, it is crucial to choose the appropriate theory. This article suggests a theoretical framework based on inclusive review of literatures to explore conceptual understanding of earthquake and earthquake preparedness among school students at Ranau, Sabah.