Articoli di riviste: "Navigation Among Movable Obstacles"

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STILMAN, MIKE, e JAMES J. KUFFNER. "NAVIGATION AMONG MOVABLE OBSTACLES: REAL-TIME REASONING IN COMPLEX ENVIRONMENTS". International Journal of Humanoid Robotics 02, n. 04 (dicembre 2005): 479–503. http://dx.doi.org/10.1142/s0219843605000545.

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Abstract (sommario):

In this paper, we address the problem of Navigation Among Movable Obstacles (NAMO): a practical extension to navigation for humanoids and other dexterous mobile robots. The robot is permitted to reconfigure the environment by moving obstacles and clearing free space for a path. This paper presents a resolution complete planner for a subclass of NAMO problems. Our planner takes advantage of the navigational structure through state-space decomposition and heuristic search. The planning complexity is reduced to the difficulty of the specific navigation task, rather than the dimensionality of the multi-object domain. We demonstrate real-time results for spaces that contain large numbers of movable obstacles. We also present a practical framework for single-agent search that can be used in algorithmic reasoning about this domain.

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Stilman, Mike, Koichi Nishiwaki, Satoshi Kagami e James J. Kuffner. "Planning and executing navigation among movable obstacles". Advanced Robotics 21, n. 14 (gennaio 2007): 1617–34. http://dx.doi.org/10.1163/156855307782227408.

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Moghaddam, Shokraneh K., e Ellips Masehian. "Planning Robot Navigation among Movable Obstacles (NAMO) through a Recursive Approach". Journal of Intelligent & Robotic Systems 83, n. 3-4 (10 febbraio 2016): 603–34. http://dx.doi.org/10.1007/s10846-016-0344-1.

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Stilman, Mike, e James Kuffner. "Planning Among Movable Obstacles with Artificial Constraints". International Journal of Robotics Research 27, n. 11-12 (novembre 2008): 1295–307. http://dx.doi.org/10.1177/0278364908098457.

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Raghavan, Vignesh Sushrutha, Dimitrios Kanoulas, Darwin G. Caldwell e Nikos G. Tsagarakis. "Reconfigurable and Agile Legged-Wheeled Robot Navigation in Cluttered Environments With Movable Obstacles". IEEE Access 10 (2022): 2429–45. http://dx.doi.org/10.1109/access.2021.3139438.

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Nobile, Luca, Marco Randazzo, Michele Colledanchise, Luca Monorchio, Wilson Villa, Francesco Puja e Lorenzo Natale. "Active Exploration for Obstacle Detection on a Mobile Humanoid Robot". Actuators 10, n. 9 (25 agosto 2021): 205. http://dx.doi.org/10.3390/act10090205.

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Abstract (sommario):

Conventional approaches to robot navigation in unstructured environments rely on information acquired from the LiDAR mounted on the robot base to detect and avoid obstacles. This approach fails to detect obstacles that are too small, or that are invisible because they are outside the LiDAR’s field of view. A possible strategy is to integrate information from other sensors. In this paper, we explore the possibility of using depth information from a movable RGB-D camera mounted on the head of the robot, and investigate, in particular, active control strategies to effectively scan the environment. Existing works combine RGBD-D and 2D LiDAR data passively by fusing the current point-cloud from the RGB-D camera with the occupancy grid computed from the 2D LiDAR data, while the robot follows a given path. In contrast, we propose an optimization strategy that actively changes the position of the robot’s head, where the camera is mounted, at each point of the given navigation path; thus, we can fully exploit the RGB-D camera to detect, and hence avoid, obstacles undetected by the 2D LiDAR, such as overhanging obstacles or obstacles in blind spots. We validate our approach in both simulation environments to gather statistically significant data and real environments to show the applicability of our method to real robots. The platform used is the humanoid robot R1.

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Ming, Zhenxing, e Hailong Huang. "A 3D Vision Cone Based Method for Collision Free Navigation of a Quadcopter UAV among Moving Obstacles". Drones 5, n. 4 (12 novembre 2021): 134. http://dx.doi.org/10.3390/drones5040134.

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In the near future, it’s expected that unmanned aerial vehicles (UAVs) will become ubiquitous surrogates for human-crewed vehicles in the field of border patrol, package delivery, etc. Therefore, many three-dimensional (3D) navigation algorithms based on different techniques, e.g., model predictive control (MPC)-based, navigation potential field-based, sliding mode control-based, and reinforcement learning-based, have been extensively studied in recent years to help achieve collision-free navigation. The vast majority of the 3D navigation algorithms perform well when obstacles are sparsely spaced, but fail when facing crowd-spaced obstacles, which causes a potential threat to UAV operations. In this paper, a 3D vision cone-based reactive navigation algorithm is proposed to enable small quadcopter UAVs to seek a path through crowd-spaced 3D obstacles to the destination without collisions. The proposed algorithm is simulated in MATLAB with different 3D obstacles settings to demonstrate its feasibility and compared with the other two existing 3D navigation algorithms to exhibit its superiority. Furthermore, a modified version of the proposed algorithm is also introduced and compared with the initially proposed algorithm to lay the foundation for future work.

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Wang, Chao, Andrey V. Savkin e Matthew Garratt. "A strategy for safe 3D navigation of non-holonomic robots among moving obstacles". Robotica 36, n. 2 (10 novembre 2017): 275–97. http://dx.doi.org/10.1017/s026357471700039x.

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SUMMARYA non-holonomic robot with a bounded control input travels in a dynamic unknown 3D environment with moving obstacles. We propose a 3D navigation strategy to reach a given final destination point while avoiding collisions with obstacles. A formal analysis of the proposed 3D robot navigation algorithm is given. Computer simulation results and experiments with a real flying autonomous vehicle confirm the applicability and performance of the proposed guidance approach.

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Foux, G., M. Heymann e A. Bruckstein. "Two-dimensional robot navigation among unknown stationary polygonal obstacles". IEEE Transactions on Robotics and Automation 9, n. 1 (1993): 96–102. http://dx.doi.org/10.1109/70.210800.

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Verma, Satish C., Siyuan Li e Andrey V. Savkin. "A Hybrid Global/Reactive Algorithm for Collision-Free UAV Navigation in 3D Environments with Steady and Moving Obstacles". Drones 7, n. 11 (13 novembre 2023): 675. http://dx.doi.org/10.3390/drones7110675.

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This paper introduces a practical navigation approach for nonholonomic Unmanned Aerial Vehicles (UAVs) in 3D environment settings with numerous stationary and dynamic obstacles. To achieve the intended outcome, Dynamic Programming (DP) is combined with a reactive control algorithm. The DP allows the UAVs to navigate among known static barriers and obstacles. Additionally, the reactive controller uses data from the onboard sensor to avoid unforeseen obstacles. The proposed strategy is illustrated through computer simulation results. In simulations, the UAV successfully navigates around dynamic obstacles while maintaining its route to the target. These results highlight the ability of our proposed approach to ensure safe and efficient UAV navigation in complex and obstacle-laden environments.

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Savkin, Andrey V., e Chao Wang. "A framework for safe assisted navigation of semi-autonomous vehicles among moving and steady obstacles". Robotica 35, n. 5 (22 gennaio 2016): 981–1005. http://dx.doi.org/10.1017/s0263574715000922.

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SUMMARYWe present a novel framework for collision free assisted navigation of a semi-autonomous vehicle in complex unknown environments with moving and steady obstacles. In the proposed system, a semi-autonomous vehicle is guided by a human operator and an automatic reactive navigator. The autonomous reactive navigation block takes control from the human operator in situations where there is the danger of collision with obstacle. A mathematically rigorous analysis of the proposed approach is provided. The performance of the proposed assisted navigation system is demonstrated via experiments with a real semi-autonomous hospital bed and extensive computer simulations.

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Pratihar, Dilip Kumar, Kalyanmoy Deb e Amitabha Ghosh. "A genetic-fuzzy approach for mobile robot navigation among moving obstacles". International Journal of Approximate Reasoning 20, n. 2 (febbraio 1999): 145–72. http://dx.doi.org/10.1016/s0888-613x(98)10026-9.

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Kim, Doug. "Networked Service Robots Control and Synchronization with Surveillance System Assistance". IAES International Journal of Robotics and Automation (IJRA) 6, n. 2 (1 giugno 2017): 80. http://dx.doi.org/10.11591/ijra.v6i2.pp80-98.

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This paper proposes an efficient navigation control and synchronization mechanism of multiple networked robots for operation in large confined areas. An adaptable grid based navigation and control strategy is adopted to eliminate potential collisions among robots. Unexpected obstacles are handled and the speed of individual robot is maintained using the node-ordering technique. The proposed navigation control and synchronization mechanism is scalable and can be easily extended for multi-cell large environment. The obstacles information is gathered through local information by the robots for better planning of the navigation. The system collaborates with the existing surveillance systems in case of additional visual information is necessary. The interaction with the surveillance system is minimized to reduce potential overhead. The proposed methodology is evaluated for a large-scale simulation with multiple robots.

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Cheng, Chuanxin, Shuang Duan, Haidong He, Xinlin Li e Yiyang Chen. "A Generalized Robot Navigation Analysis Platform (RoNAP) with Visual Results Using Multiple Navigation Algorithms". Sensors 22, n. 23 (22 novembre 2022): 9036. http://dx.doi.org/10.3390/s22239036.

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The robotic navigation task is to find a collision-free path among a mass of stationary or migratory obstacles. Various well-established algorithms have been applied to solve navigation tasks. It is necessary to test the performance of designed navigation algorithms in practice. However, it seems an extremely unwise choice to implement them in a real environment directly unless their performance is guaranteed to be acceptable. Otherwise, it takes time to test navigation algorithms because of a long training process, and imperfect performance may cause damage if the robot collides with obstacles. Hence, it is of key significance to develop a mobile robot analysis platform to simulate the real environment which has the ability to replicate the exact application scenario and be operated in a simple manner. This paper introduces a brand new analysis platform named robot navigation analysis platform (RoNAP), which is an open-source platform developed using the Python environment. A user-friendly interface supports its realization for the evaluation of various navigation algorithms. A variety of existing algorithms were able to achieve desired test results on this platform, indicating its feasibility and efficiency for navigation algorithm analysis.

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Yamamoto, Motoji, Nobuhiro Ushimi e Akira Mohri. "Development of Sensor-Based Navigation for Mobile Robots Using Target Direction Sensor". Journal of Robotics and Mechatronics 11, n. 1 (20 febbraio 1999): 39–44. http://dx.doi.org/10.20965/jrm.1999.p0039.

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Sensor-based navigation used a target direction sensor for mobile robots among unknown obstacles in work space is discussed. The advantage of target direction information is robustness of measurement error for online navigation, compared to robot location information. Convergence of navigation using target direction information is discussed. An actual sensor system using two CdS sensors to measure target direction is proposed. Using target direction information, we present a new sensor based navigation algorithm in unknown obstacle environment. The navigation algorithm is based on target direction information, unlike sensor-based motion planning algorithms based on mobile robot location information. Using a sensor-based navigation system, we conducted a navigation experiment and simulations in unknown obstacle environment.

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Hassan, Sunzid, Lingxiao Wang e Khan Raqib Mahmud. "Robotic Odor Source Localization via Vision and Olfaction Fusion Navigation Algorithm". Sensors 24, n. 7 (5 aprile 2024): 2309. http://dx.doi.org/10.3390/s24072309.

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Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. An effective navigation algorithm that guides the robot to approach the odor source is the key to successfully locating the odor source. While traditional OSL approaches primarily utilize an olfaction-only strategy, guiding robots to find the odor source by tracing emitted odor plumes, our work introduces a fusion navigation algorithm that combines both vision and olfaction-based techniques. This hybrid approach addresses challenges such as turbulent airflow, which disrupts olfaction sensing, and physical obstacles inside the search area, which may impede vision detection. In this work, we propose a hierarchical control mechanism that dynamically shifts the robot’s search behavior among four strategies: crosswind maneuver, Obstacle-Avoid Navigation, Vision-Based Navigation, and Olfaction-Based Navigation. Our methodology includes a custom-trained deep-learning model for visual target detection and a moth-inspired algorithm for Olfaction-Based Navigation. To assess the effectiveness of our approach, we implemented the proposed algorithm on a mobile robot in a search environment with obstacles. Experimental results demonstrate that our Vision and Olfaction Fusion algorithm significantly outperforms vision-only and olfaction-only methods, reducing average search time by 54% and 30%, respectively.

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Matveev, Alexey S., Michael C. Hoy e Andrey V. Savkin. "A globally converging algorithm for reactive robot navigation among moving and deforming obstacles". Automatica 54 (aprile 2015): 292–304. http://dx.doi.org/10.1016/j.automatica.2015.02.012.

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Large, Frédéric, Christian Laugier e Zvi Shiller. "Navigation Among Moving Obstacles Using the NLVO: Principles and Applications to Intelligent Vehicles". Autonomous Robots 19, n. 2 (settembre 2005): 159–71. http://dx.doi.org/10.1007/s10514-005-0610-8.

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Esquivel, Wilson D., e Luciano E. Chiang. "Nonholonomic path planning among obstacles subject to curvature restrictions". Robotica 20, n. 1 (gennaio 2002): 49–58. http://dx.doi.org/10.1017/s0263574701003630.

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This paper addresses the problem of finding a nonholonomic path subject to a curvature restriction, to be tracked by a wheeled autonomous navigation vehicle. This robot is able to navigate in a structured environment, with obstacles modeled as polygons, thus constituting a model based system. The path planning methodology begins with the conditioning of the polygonal environment by offsetting each polygon in order to avoid the possibility of collision with the mobile. Next, the modified polygonal environment is used to compute a preliminary shortest path (PA) between the two extreme positions of the trajectory in the plane (x, y). This preliminary path (PA) does not yet consider the restrictions on the curvature and is formed only by straight line segments. A smoothing process follows in order to obtain a path (PS) that satisfies curvature restrictions which consist basically of joining the straight line segments by circular arcs of minimum radius R (filleting). Finally, the initial and final orientation of the vehicle are accounted for. This is done using a technique we have called the Star Algorithm, because of the geometric shape of the resulting maneuvers. A final complete path (PC) is thus obtained.

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AYAZ, YASAR, KHALID MUNAWAR, MOHAMMAD BILAL MALIK, ATSUSHI KONNO e MASARU UCHIYAMA. "HUMAN-LIKE APPROACH TO FOOTSTEP PLANNING AMONG OBSTACLES FOR HUMANOID ROBOTS". International Journal of Humanoid Robotics 04, n. 01 (marzo 2007): 125–49. http://dx.doi.org/10.1142/s0219843607000960.

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Unlike wheeled robots, humanoid robots are able to cross obstacles by stepping over or upon them. Conventional 2D methods for robot navigation fail to exploit this unique ability of humanoids and thus design trajectories only by circumventing obstacles. Recently, global algorithms have been presented that take into account this feature of humanoids. However, due to high computational complexity, most of them are very time consuming. In this paper, we present a new approach to footstep planning in obstacle cluttered environments that employs a human-like strategy to terrain traversal. Simulation results of its implementation on a model of the Saika-3 humanoid robot are also presented. The algorithm, being one of reactive nature, refutes previous claims that reactive algorithms fail to find successful paths in complex obstacle cluttered environments.

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Asensio, J. R., J. M. M. Montiel e L. Montano. "Navigation Among Obstacles by the Cooperation of Trinocular Stereo Vision System and Laser Rangefinder". IFAC Proceedings Volumes 31, n. 3 (marzo 1998): 285–90. http://dx.doi.org/10.1016/s1474-6670(17)44099-7.

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Hui, Nirmal Baran, e Dilip Kumar Pratihar. "Soft Computing-Based Navigation Schemes for a Real Wheeled Robot Moving Among Static Obstacles". Journal of Intelligent and Robotic Systems 51, n. 3 (21 dicembre 2007): 333–68. http://dx.doi.org/10.1007/s10846-007-9190-5.

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Kim, Changwon, e Jong-Seob Won. "A Fuzzy Analytic Hierarchy Process and Cooperative Game Theory Combined Multiple Mobile Robot Navigation Algorithm". Sensors 20, n. 10 (16 maggio 2020): 2827. http://dx.doi.org/10.3390/s20102827.

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This study presents a multi-robot navigation strategy based on a multi-objective decision-making algorithm, the Fuzzy Analytic Hierarchy Process (FAHP). FAHP analytically selects an optimal position as a sub-goal among points on the sensing boundary of a mobile robot considering the following three objectives: the travel distance to the target, collision safety with obstacles, and the rotation of the robot to face the target. Alternative solutions are evaluated by quantifying the relative importance of the objectives. As the FAHP algorithm is insufficient for multi-robot navigation, cooperative game theory is added to improve it. The performance of the proposed multi-robot navigation algorithm is tested with up to 12 mobile robots in several simulation conditions, altering factors such as the number of operating robots and the warehouse layout.

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Filimonov, A. B., e N. B. Filimonov. "Issues of Motion Control of Mobile Robots Based on the Potential Guidance Method". Mekhatronika, Avtomatizatsiya, Upravlenie 20, n. 11 (7 novembre 2019): 677–85. http://dx.doi.org/10.17587/mau.20.677-685.

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One of the topical areas of research in modern robotics is the problem of local navigation of mobile robots (MR), which ensures the movement of the robot to the target with the bypass of obstacles in the process of movement. The navigation process includes the following steps: mapping the environment, localization of the robot and planning the route leading to the goal. Among the popular methods of local navigation of robots is the method of artificial potential fields (PF). The essence of the PF method is to implement the movement of the MR in the field of "information forces" using the forces of "attraction" to the target position and the forces of "repulsion" from obstacles.This article addresses the issues of local navigation and motion control of the MR based on the method of PF.When using traditional attracting potential forces, the structure of virtual forces near the obstacle depends on the distance of the MR from the target, and the robot movement will slow down at the end of the route, which will inevitably lead to an unjustified tightening of the total time of moving the robot to the target position. To eliminate this undesirable effect, the authors propose to use attracting potential fields of special type.The authors propose new methods of PF allowing to solve the key problems for the control of MR — "traps" (potential pits) and bypass obstacles: the method of two maps of potential fields and the method of "fairway" on the map of potential fields. The methods of "beetle" for solving the problem of bypass obstacles in the condition of the absence of a priori information about the working space of MR are discussed. A modified method of "beetle" having a number of advantages in comparison with classical methods is proposed.

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Garrett, Caelan Reed, Tomás Lozano-Pérez e Leslie Pack Kaelbling. "FFRob: Leveraging symbolic planning for efficient task and motion planning". International Journal of Robotics Research 37, n. 1 (12 novembre 2017): 104–36. http://dx.doi.org/10.1177/0278364917739114.

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Mobile manipulation problems involving many objects are challenging to solve due to the high dimensionality and multi-modality of their hybrid configuration spaces. Planners that perform a purely geometric search are prohibitively slow for solving these problems because they are unable to factor the configuration space. Symbolic task planners can efficiently construct plans involving many variables but cannot represent the geometric and kinematic constraints required in manipulation. We present the FFRob algorithm for solving task and motion planning problems. First, we introduce extended action specification (EAS) as a general purpose planning representation that supports arbitrary predicates as conditions. We adapt existing heuristic search ideas for solving strips planning problems, particularly delete-relaxations, to solve EAS problem instances. We then apply the EAS representation and planners to manipulation problems resulting in FFRob. FFRob iteratively discretizes task and motion planning problems using batch sampling of manipulation primitives and a multi-query roadmap structure that can be conditionalized to evaluate reachability under different placements of movable objects. This structure enables the EAS planner to efficiently compute heuristics that incorporate geometric and kinematic planning constraints to give a tight estimate of the distance to the goal. Additionally, we show FFRob is probabilistically complete and has a finite expected runtime. Finally, we empirically demonstrate FFRob’s effectiveness on complex and diverse task and motion planning tasks including rearrangement planning and navigation among movable objects.

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Cardona, Gustavo A., e Juan M. Calderon. "Robot Swarm Navigation and Victim Detection Using Rendezvous Consensus in Search and Rescue Operations". Applied Sciences 9, n. 8 (25 aprile 2019): 1702. http://dx.doi.org/10.3390/app9081702.

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Cooperative behaviors in multi-robot systems emerge as an excellent alternative for collaboration in search and rescue tasks to accelerate the finding survivors process and avoid risking additional lives. Although there are still several challenges to be solved, such as communication between agents, power autonomy, navigation strategies, and detection and classification of survivors, among others. The research work presented by this paper focuses on the navigation of the robot swarm and the consensus of the agents applied to the victims detection. The navigation strategy is based on the application of particle swarm theory, where the robots are the agents of the swarm. The attraction and repulsion forces that are typical in swarm particle systems are used by the multi-robot system to avoid obstacles, keep group compact and navigate to a target location. The victims are detected by each agent separately, however, once the agents agree on the existence of a possible victim, these agents separate from the general swarm by creating a sub-swarm. The sub-swarm agents use a modified rendezvous consensus algorithm to perform a formation control around the possible victims and then carry out a consensus of the information acquired by the sensors with the aim to determine the victim existence. Several experiments were conducted to test navigation, obstacle avoidance, and search for victims. Additionally, different situations were simulated with the consensus algorithm. The results show how swarm theory allows the multi-robot system navigates avoiding obstacles, finding possible victims, and settling down their possible use in search and rescue operations.

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Manor, Gil, e Elon Rimon. "The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints". Autonomous Robots 41, n. 2 (12 febbraio 2016): 385–400. http://dx.doi.org/10.1007/s10514-015-9538-9.

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Njah, Malek, e Mohamed Jallouli. "Fuzzy-EKF Controller for Intelligent Wheelchair Navigation". Journal of Intelligent Systems 25, n. 2 (1 aprile 2016): 107–21. http://dx.doi.org/10.1515/jisys-2014-0139.

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AbstractThe electric wheelchair gives more autonomy and facilitates movement for handicapped persons in the home or in a hospital. Among the problems faced by these persons are collision with obstacles, the doorway, the navigation in a hallway, and reaching the desired place. These problems are due to the difficult manipulation of an electric wheelchair, especially for persons with severe disabilities. Hence, we tried to add more functionality to the standard wheelchair in order to increase movement range, security, environment access, and comfort. In this context, we have developed an automatic control method for indoor navigation. The proposed control system is mounted on the electric wheelchair for the handicapped, developed in the research laboratory CEMLab (Control and Energy Management Laboratory-Tunisia). The proposed method is based on two fuzzy controllers that ensure target achievement and obstacle avoidance. Furthermore, an extended Kalman filter was used to provide precise measurements and more effective data fusion localization. In this paper, we present the simulation and experimental results of the wheelchair navigation system.

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KAKIUCHI, Yohei, Ryohei UEDA, Kei OKADA e Masayuki INABA. "2A2-E06 Performing Among Movable Obstacles Using On-Line Reconstruction of Environment Recognition With Active Sensing and Color Range Sensor". Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2010 (2010): _2A2—E06_1—_2A2—E06_4. http://dx.doi.org/10.1299/jsmermd.2010._2a2-e06_1.

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Nikoohemat, S., A. Diakité, S. Zlatanova e G. Vosselman. "INDOOR 3D MODELING AND FLEXIBLE SPACE SUBDIVISION FROM POINT CLOUDS". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (29 maggio 2019): 285–92. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-285-2019.

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Abstract (sommario):

<p><strong>Abstract.</strong> Indoor navigation can be a tedious process in a complex and unknown environment. It gets more critical when the first responders try to intervene in a big building after a disaster has occurred. For such cases, an accurate map of the building is among the best supports possible. Unfortunately, such a map is not always available, or generally outdated and imprecise, leading to error prone decisions. Thanks to advances in the laser scanning, accurate 3D maps can be built in relatively small amount of time using all sort of laser scanners (stationary, mobile, drone), although the information they provide is generally an unstructured point cloud. While most of the existing approaches try to extensively process the point cloud in order to produce an accurate architectural model of the scanned building, similar to a Building Information Model (BIM), we have adopted a space-focused approach. This paper presents our framework that starts from point-clouds of complex indoor environments, performs advanced processes to identify the 3D structures critical to navigation and path planning, and provides fine-grained navigation networks that account for obstacles and spatial accessibility of the navigating agents. The method involves generating a volumetric-wall vector model from the point cloud, identifying the obstacles and extracting the navigable 3D spaces. Our work contributes a new approach for space subdivision without the need of using laser scanner positions or viewpoints. Unlike 2D cell decomposition or a binary space partitioning, this work introduces a space enclosure method to deal with 3D space extraction and non-Manhattan World architecture. The results show more than 90% of spaces are correctly extracted. The approach is tested on several real buildings and relies on the latest advances in indoor navigation.</p>

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Wild Thomas, Devin, Wheeler Ruml e Solomon Eyal Shimony. "Real-time Safe Interval Path Planning". Proceedings of the International Symposium on Combinatorial Search 17 (1 giugno 2024): 161–69. http://dx.doi.org/10.1609/socs.v17i1.31554.

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Abstract (sommario):

Navigation among dynamic obstacles is a fundamental task in robotics that has been modeled in various ways. In Safe Interval Path Planning, location is discretized to a grid, time is continuous, future trajectories of obstacles are assumed known, and planning takes place offline. In this work, we define the Real-time Safe Interval Path Planning problem setting, in which the agent plans online and must issue its next action within a strict time bound. Unlike in classical real-time heuristic search, the cost-to-go in Real-time Safe Interval Path Planning is a function of time rather than a scalar. We present several algorithms for this setting and prove that they learn admissible heuristics. Empirical evaluation shows that the new methods perform better than classical approaches under a variety of conditions.

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Krejsa, Jiri, Stanislav Vĕchet e Tomas Ripel. "Neural Network Based Reactive Navigation for Mobile Robot in Dynamic Environment". Solid State Phenomena 198 (marzo 2013): 108–13. http://dx.doi.org/10.4028/www.scientific.net/ssp.198.108.

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When mobile robots are used among people, the best accepted motion related behavior is a human-like motion of the robot. Such behavior is difficult to obtain with commonly used finite state machine based planners, but can easily be evoked when human controls the robot. The paper presents the way of transforming such knowledge from human controller to reactive planner in the robot navigation module. Reactive planner is based on machine learning, neural networks in particular. The planner consists of two separate neural networks, one serving as predictor of dynamic obstacles behavior, second one serving as the reactive planner itself, producing desirable actions of the robot both in terms of velocity and direction. Planner was verified on real robot producing human-like behavior when used in real environment.

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Ramezani Dooraki, Amir. "A survey on computer vision technology in Camera Based ETA devices". International Journal of Advances in Intelligent Informatics 1, n. 3 (30 novembre 2015): 115. http://dx.doi.org/10.26555/ijain.v1i3.40.

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Electronic Travel Aid systems are expected to make impaired persons able to perform their everyday tasks such as finding an object and avoiding obstacles easier. Among ETA devices, Camera Based ETA devices are the new one and with a high potential for helping Visually Impaired Persons. With recent advances in computer science and specially computer vision, Camera Based ETA devices used several computer vision algorithms and techniques such as object recognition and stereo vision in order to help VIP to perform tasks such as reading banknotes, recognizing people and avoiding obstacles. This paper analyses and appraises a number of literatures in this area with focus on stereo vision technique. Finally, after discussing about the methods and techniques used in different literatures, it is concluded that the stereo vision is the best technique for helping VIP in their everyday navigation.

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Yue-wen, Fu, Li Meng, Liang Jia-hong e Hu Xiao-qian. "Optimal Acceleration-Velocity-Bounded Trajectory Planning in Dynamic Crowd Simulation". Journal of Applied Mathematics 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/501689.

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Creating complex and realistic crowd behaviors, such as pedestrian navigation behavior with dynamic obstacles, is a difficult and time consuming task. In this paper, we study one special type of crowd which is composed of urgent individuals, normal individuals, and normal groups. We use three steps to construct the crowd simulation in dynamic environment. The first one is that the urgent individuals move forward along a given path around dynamic obstacles and other crowd members. An optimal acceleration-velocity-bounded trajectory planning method is utilized to model their behaviors, which ensures that the durations of the generated trajectories are minimal and the urgent individuals are collision-free with dynamic obstacles (e.g., dynamic vehicles). In the second step, a pushing model is adopted to simulate the interactions between urgent members and normal ones, which ensures that the computational cost of the optimal trajectory planning is acceptable. The third step is obligated to imitate the interactions among normal members using collision avoidance behavior and flocking behavior. Various simulation results demonstrate that these three steps give realistic crowd phenomenon just like the real world.

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Montiel, Holman, Fernando Martínez e Fredy Martínez. "Parallel control model for navigation tasks on service robots". Journal of Physics: Conference Series 2135, n. 1 (1 dicembre 2021): 012002. http://dx.doi.org/10.1088/1742-6596/2135/1/012002.

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Abstract Autonomous mobility remains an open research problem in robotics. This is a complex problem that has its characteristics according to the type of task and environment intended for the robot’s activity. Service robotics has in this sense problems that have not been solved satisfactorily. These robots must interact with human beings in environments designed for human beings, which implies that one of the basic sensors for structuring motion control and navigation schemes are those that replicate the human optical sense. In their normal activity, robots are expected to interpret visual information in the environment while following a certain motion policy that allows them to move from one point to another in the environment, consistent with their tasks. A good optical sensing system can be structured around digital cameras, with which it can apply visual identification routines of both the trajectory and its environment. This research proposes a parallel control scheme (with two loops) for the definition of movements of a service robot from images. On the one hand, there is a control loop based on a visual memory strategy using a convolutional neural network. This system contemplates a deep learning model that is trained from images of the environment containing characteristic elements of the navigation environment (various types of obstacles and different cases of free trajectories with and without navigation path). To this first loop is connected in parallel a second loop in charge of defining the specific distances to the obstacles using a stereo vision system. The objective of this parallel loop is to quickly identify the obstacle points in front of the robot from the images using a bacterial interaction model. These two loops form an information feedback motion control framework that quickly analyzes the environment and defines motion strategies from digital images, achieving real-time control driven by visual information. Among the advantages of our scheme are the low processing and memory costs in the robot, and the no need to modify the environment to facilitate the navigation of the robot. The performance of the system is validated by simulation and laboratory experiments.

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Tanaka, Takayuki, Kazuo Yamafuji e Hidenori Takahashi. "Development of the Intelligent Mobile Robot for Service Use Report 1: Environmental-Adjustable Autonomous Locomotion Control System". Journal of Robotics and Mechatronics 9, n. 4 (20 agosto 1997): 275–82. http://dx.doi.org/10.20965/jrm.1997.p0275.

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We have developed an intelligent mobile robot for use as an office “secretary/ helper” by day and “security maintenance guard” by night. The robot’s autonomous locomotion control system (ALCS) plans its paths, recognizes absolute positions and learns navigation control. To aid the robot in moving more appropriately and smoothly among human beings and obstacles in an office environment, we studied learning by a fuzzy neural network that tunes membership functions for fuzzy locomotion control, i.e., the intelligent robot learns to move autonomously through its surroundings. Results obtained by computer simulation show the proposed method is useful in autonomous robot locomotion control.

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Barri, Eirini, Christos John Bouras, Apostolos Gkamas e Spyridon Aniceto Katsampiris Salgado. "GuideMe". International Journal of Smart Sensor Technologies and Applications 1, n. 2 (aprile 2020): 36–53. http://dx.doi.org/10.4018/ijssta.2020040103.

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The interest for indoor navigational systems is expanding daily with concerns among visually impaired people who cannot navigate safely indoors. The main goal of such systems is the localization and direction of the individual who has a wearable device that provides voice commands to navigate indoor buildings. This paper aims to present the design and the implementation of the GuideMe project. The GuideMe project's goal is the design, implementation, and evaluation of a navigation system focused on people who face troubles in indoor moving utilizing a wearable device. Specifically, the focus group is people suffering from visual impairment. The person carrying the wearable device takes guidelines about the location from indoor ultrawide band (UWB) anchors. The commands provided are about indoor direction through voice commands, assisting him to avoid obstacles in his route. The authors present the architecture and the details of the various modules, which consist of the proposed indoor navigation system, and some initial evaluations of the proposed system yielding promising results.

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Parhi, Dayal R., e S. Kundu. "Navigational control of underwater mobile robot using dynamic differential evolution approach". Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment 231, n. 1 (3 agosto 2016): 284–301. http://dx.doi.org/10.1177/1475090216642465.

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This article focuses on the navigational control of underwater mobile robot. Differential evolution approach has been used to navigate the underwater robot from source to destination while avoiding various types of obstacles. Differential evolution algorithm has been employed to find out the robot’s global best pose among a set of possible solutions based on the fitness value with respect to the current sensory data about obstacles and target. Such evolutionary computation scheme can provide desirable convergence, diversity and also robustness depending on proper selection and adaptive tuning of parameters. Self-learning ability of the parameters in the path planning algorithm is crucial to deal with nonlinearities and ambiguities of hydrodynamics as created by high-frequency oscillations during underwater motion. A sequence of intermediate positions chosen by proposed dynamic differential evolution algorithm between start and goal points can be defined as a near-optimum path for underwater robot. During navigation of the robot, the path smoothness and clearance from obstacles and computational time are also considered for performance evaluation of implemented algorithm. The feasibility of the proposed underwater motion planning approach has been authenticated through the simulation and experimental results.

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Yakovlev, K. S., A. A. Andreychuk, J. S. Belinskaya e D. A. Makarov. "Safe Interval Path Planning and Flatness-Based Control for Navigation of a Mobile Robot among Static and Dynamic Obstacles". Automation and Remote Control 83, n. 6 (giugno 2022): 903–18. http://dx.doi.org/10.1134/s000511792206008x.

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Panwar, Vikas Singh, Anish Pandey e Muhammad Ehtesham Hasan. "Generalised Regression Neural Network (GRNN) Architecture-Based Motion Planning and Control of an E-Puck Robot in V-REP Software Platform". Acta Mechanica et Automatica 15, n. 4 (29 novembre 2021): 209–14. http://dx.doi.org/10.2478/ama-2021-0027.

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Abstract This article focuses on the motion planning and control of an automated differential-driven two-wheeled E-puck robot using Generalized Regression Neural Network (GRNN) architecture in the Virtual Robot Experimentation Platform (V-REP) software platform among scattered obstacles. The main advantage of this GRNN over the feedforward neural network is that it provides accurate results in a short period with minimal error. First, the designed GRNN architecture receives real-time obstacle information from the Infra-Red (IR) sensors of an E-puck robot. According to IR sensor data interpretation, this architecture sends the left and right wheel velocities command to the E-puck robot in the V-REP software platform. In the present study, the GRNN architecture includes the MIMO system, i.e., multiple inputs (IR sensors data) and multiple outputs (left and right wheel velocities). The three-dimensional (3D) motion and orientation results of the GRNN architecture-controlled E-puck robot are carried out in the V-REP software platform among scattered and wall-type obstacles. Further on, compared with the feedforward neural network, the proposed GRNN architecture obtains better navigation path length with minimum error results.

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Tolis, Fotios C., Panagiotis S. Trakas, Taxiarchis-Foivos Blounas, Christos K. Verginis e Charalampos P. Bechlioulis. "Learning to Execute Timed-Temporal-Logic Navigation Tasks under Input Constraints in Obstacle-Cluttered Environments". Robotics 13, n. 5 (26 aprile 2024): 65. http://dx.doi.org/10.3390/robotics13050065.

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This study focuses on addressing the problem of motion planning within workspaces cluttered with obstacles while considering temporal and input constraints. These specifications can encapsulate intricate high-level objectives involving both temporal and spatial constraints. The existing literature lacks the ability to fulfill time specifications while simultaneously managing input-saturation constraints. The proposed approach introduces a hybrid three-component control algorithm designed to learn the safe execution of a high-level specification expressed as a timed temporal logic formula across predefined regions of interest in the workspace. The first component encompasses a motion controller enabling secure navigation within the minimum allowable time interval dictated by input constraints, facilitating the abstraction of the robot’s motion as a timed transition system between regions of interest. The second component utilizes formal verification and convex optimization techniques to derive an optimal high-level timed plan over the mentioned transition system, ensuring adherence to the agent’s specification. However, the necessary navigation times and associated costs among regions are initially unknown. Consequently, the algorithm’s third component iteratively adjusts the transition system and computes new plans as the agent navigates, acquiring updated information about required time intervals and associated navigation costs. The effectiveness of the proposed scheme is demonstrated through both simulation and experimental studies.

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Agayev, N. B., Q. H. Orujov e N. N. Kalbiyev. "Planning the Optimal Reference Flight Path of an Aircraft Using a Terrain Map". Mekhatronika, Avtomatizatsiya, Upravlenie 24, n. 9 (4 settembre 2023): 496–502. http://dx.doi.org/10.17587/mau.24.496-502.

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In connection with the development of aviation technology, the expansion of the functionality of modern aircraft and the complication of the tasks being solved, additional stringent requirements are imposed on the accuracy of air navigation. Along with high accuracy, navigation autonomy is also required. The autonomy of aircraft navigation implies the navigation of an aircraft without the use of active radar facilities. In this article, to calculate the optimal reference flight path of an aircraft in a horizontal plane, the Bellman dynamic programming method is proposed using a digital terrain map. A technique, algorithms have been developed, and a numerical experiment has been carried out using fragments of a digital terrain map. High accuracy and autonomy of navigation are necessary, among other things, to ensure stealth (invisibility) of aircraft by ground-based radar facilities of a potential enemy in low-altitude flight mode. The best stealth of an aircraft flight in a low-altitude flight mode is achieved not only by flying around, but also by avoiding obstacles, due to the shielding properties of the earth’s surface. Autonomy of navigation provides periodic correction of the reference flight path during long-term flight, and high accuracy prevents aircraft collisions with the earth’s surface in low-altitude flight mode. The purpose of this work is to select the optimal reference trajectory (route) of an aircraft flight in the low-altitude flight mode. This article discusses a method developed based on the principle of dynamic programming for calculating the reference flight path in the horizontal plane depending on the DEM and the implementation of the algorithm based on the proposed method with a specific numerical example. The method makes it possible to calculate the optimal flight route, which provides the greatest secrecy of the aircraft in the low-altitude flight mode using the screening properties of the earth’s surface irregularities.

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P Kalidas, Amudhini, Christy Jackson Joshua, Abdul Quadir Md, Shakila Basheer, Senthilkumar Mohan e Sapiah Sakri. "Deep Reinforcement Learning for Vision-Based Navigation of UAVs in Avoiding Stationary and Mobile Obstacles". Drones 7, n. 4 (1 aprile 2023): 245. http://dx.doi.org/10.3390/drones7040245.

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Unmanned Aerial Vehicles (UAVs), also known as drones, have advanced greatly in recent years. There are many ways in which drones can be used, including transportation, photography, climate monitoring, and disaster relief. The reason for this is their high level of efficiency and safety in all operations. While the design of drones strives for perfection, it is not yet flawless. When it comes to detecting and preventing collisions, drones still face many challenges. In this context, this paper describes a methodology for developing a drone system that operates autonomously without the need for human intervention. This study applies reinforcement learning algorithms to train a drone to avoid obstacles autonomously in discrete and continuous action spaces based solely on image data. The novelty of this study lies in its comprehensive assessment of the advantages, limitations, and future research directions of obstacle detection and avoidance for drones, using different reinforcement learning techniques. This study compares three different reinforcement learning strategies—namely, Deep Q-Networks (DQN), Proximal Policy Optimization (PPO), and Soft Actor-Critic (SAC)—that can assist in avoiding obstacles, both stationary and moving; however, these strategies have been more successful in drones. The experiment has been carried out in a virtual environment made available by AirSim. Using Unreal Engine 4, the various training and testing scenarios were created for understanding and analyzing the behavior of RL algorithms for drones. According to the training results, SAC outperformed the other two algorithms. PPO was the least successful among the algorithms, indicating that on-policy algorithms are ineffective in extensive 3D environments with dynamic actors. DQN and SAC, two off-policy algorithms, produced encouraging outcomes. However, due to its constrained discrete action space, DQN may not be as advantageous as SAC in narrow pathways and twists. Concerning further findings, when it comes to autonomous drones, off-policy algorithms, such as DQN and SAC, perform more effectively than on-policy algorithms, such as PPO. The findings could have practical implications for the development of safer and more efficient drones in the future.

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Doolan-Noble, Fiona, Danielle Smith, Robin Gauld, Debra L. Waters, Anthony Cooke e Helen Reriti. "Evolution of a health navigator model of care within a primary care setting: a case study". Australian Health Review 37, n. 4 (2013): 523. http://dx.doi.org/10.1071/ah12038.

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Objective. Patient navigation originated as an approach for reducing disparities in cancer care and consequent health outcomes. Over time navigator models have evolved and been used to address various health issues in differing contexts. This case study outlines the evolution, purpose and effects of a lay-led health navigator model in a deprived, sparsely populated, New Zealand rural setting, where primary care services are frequently understaffed and routinely overstretched. Methods. Routinely collected service utilisation data, survey results and health navigator interview data were utilised to illustrate the client group the service works with, why primary care refer to the service, as well as lessons learned from implementation to ongoing service provision. Results. Those referred to the navigator service generally represented the most vulnerable in the community. Survey respondents, overall, were highly satisfied with the service. Navigators identified barriers and facilitators to implementation, as well as ongoing obstacles and enablers to service provision. Conclusions. This lay-led navigator service provided support to a group of unwell individuals, with few resources and multiple barriers to negotiate, and has effectively engaged with health and social care services, while overcoming various barriers and obstacles to its establishment and ongoing operation. What is known about the topic? Patient navigation models of care were first employed in the 1990s, as a strategy to increase the uptake of cancer screening among disadvantaged women. They have since expanded across the cancer care continuum, but despite favourable findings, information regarding their potential in other settings is limited. What does this paper add? This paper provides a perspective on lay-led navigation services within a rural New Zealand primary care setting. The views of primary care professionals regarding the role and value of the service are provide, as is a summary of the key lessons learnt over the implementation, establishment and ongoing service delivery phases of the programme. What are the implications for practitioners? This case study proposes that lay-led navigation services can provide practical support to primary care; assisting it to meet the needs of patients living with multiple chronic conditions and social challenges.

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Wang, Renqiang, Keyin Miao, Qinrong Li, Jianming Sun e Hua Deng. "The path planning of collision avoidance for an unmanned ship navigating in waterways based on an artificial neural network". Nonlinear Engineering 11, n. 1 (1 gennaio 2022): 680–92. http://dx.doi.org/10.1515/nleng-2022-0260.

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Abstract Designing a safe, collision-free navigation route is critical for unmanned ships. This article applies the path planning method to the generation of collision avoidance paths for unmanned ships. Since the path length function is obtained from the distribution points constructed in space, it is necessary to transfer the safe domain of the unmanned ship to the obstacle, treating the unmanned ship as a particle. Then, the constructed artificial neural network (ANN) is applied to compute the collision penalty function for distribution points and obstacles. Furthermore, an evaluation function including the path length function and collision penalty function is designed, and the optimal path is obtained by computing the minimum value of the evaluation function. Meanwhile, the simulated annealing method is introduced to optimize the activation function of the output layer of the ANN to improve its classification performance and suppress the local minima problem. Finally, the application of ANN in ship autonomous dynamic collision avoidance path planning is demonstrated in two types of experiments. Among them, when avoiding static obstacles, the minimum safe passing distance between the two ships reaches 30 m; when avoiding dynamic obstacles (navigating ships), the minimum safe passing distances between the two ships in the head-on situation and the overtaking situation are 378 and 430 m, respectively.

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Rahman, Muhammad Arinal, e Moch Nurdin. "AN INVESTIGATION OF THE UTILISATION OF ENGLISH IN THE INTERNSHIP PROGRAMS AMONG THE CADETS OF NUSANTARA MARITIME ACADEMY". Pena Jangkar 3, n. 1 (30 settembre 2023): 22–40. http://dx.doi.org/10.54315/penajangkar.v3i1.63.

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This study aims to examine the utilisation of the English language within the context of the internship programme for maritime cadets, utilising interviews and observations as primary data collection methods. This qualitative research endeavour seeks to offer valuable insights into the role of English language in the internship program for maritime professionals. The findings of this study have made significant contributions to the improvement of language training programmes, communication protocols, and overall safety and efficiency in maritime internship settings. The empirical evidence indicates that possessing a strong command of English is essential for successfully carrying out safety drills, ensuring smooth vessel navigation and engine maintenance, fostering intercultural comprehension and efficient collaboration, and overseeing documentation procedures in port operations. The study places significant emphasis on the necessity of efficient language instruction, the resolution of language-related obstacles, and the facilitation of intercultural dialogue in order to adequately equip maritime academies and internship programs for fruitful internships and prospective careers as skilled and capable seafarers.

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Perlson, Jacob, Blake Kruger, Sravanthi Padullaparti, Elizabeth Eccles e Tim Lahey. "1290. A Model for “At-Distance” PrEP Navigation: Acceptability and Early Insights". Open Forum Infectious Diseases 5, suppl_1 (novembre 2018): S394. http://dx.doi.org/10.1093/ofid/ofy210.1123.

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Abstract Background HIV pre-exposure prophylaxis (PrEP) awareness and uptake among at-risk individuals remains suboptimal despite clear evidence of efficacy. Health navigators and peer educators have been employed to facilitate linkage and retention in many aspects of HIV prevention and care, including to improve PrEP utilization. Yet, the use of health navigators to improve PrEP utilization has not been well-explored in rural areas where unique challenges to HIV care have been well documented. Little is known, too, about how telemedicine may strengthen these efforts. We assessed acceptability and evaluated a health navigation program that primarily engages clients through at-distance technology-based methods. Methods To guide the design and implementation of a pilot PrEP tele-navigation program, we conducted a survey in at-risk clients contacted through social networks and at a state-funded STI clinic in New Hampshire. Approximately nine months after the launch of the navigation platform, we analyzed characteristics of client-navigator interactions. Feedback surveys were distributed to clients 3 months following engagement with the navigator. Results From July 2017 to April 2018, 139 individuals engaged the navigator program via email, text, chat, phone call, or in-person. Among the most common services provided were PrEP counseling (n = 63 or 45% of inquiries), referral to STI/HIV testing (22%), and risk reduction counseling (19%). Eight clients have been linked to PrEP care to-date. Qualitative analysis of client-navigator interactions revealed a variety of recurring barriers expressed by clients including concerns maintaining confidentiality with parents and partners, side effects of PrEP, and financial constraints. Clients provided suggestions for program improvement and indicated they felt engagement with the program increased knowledge of PrEP as well as linkage to testing and HIV prevention services. Conclusion Our pilot program highlighted the diverse obstacles to PrEP utilization in at-risk rural clients, and suggests at-distance PrEP navigation and telemedicine can support improved PrEP utilization in the rural United States. Such a navigator program should be equipped to engage clients along the PrEP care continuum. Disclosures All authors: No reported disclosures.

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Zaccone, R., e M. Martelli. "Interaction between COLREG-compliant collision avoidance systems in a multiple MASS scenario". Journal of Physics: Conference Series 2618, n. 1 (1 ottobre 2023): 012006. http://dx.doi.org/10.1088/1742-6596/2618/1/012006.

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Abstract The transportation systems are heading towards increasing autonomy in all domains, and the maritime field makes no exception. The International Maritime Organization has been working on releasing a regulatory framework for Maritime Autonomous Surface Ships (MASS) to keep pace with the technological developments in the field. Autonomous shipping forces the researcher and the designers to face a wide range of scientific challenges, such as navigation decision support systems, collision avoidance algorithms, path planning, navigation and control, sensor data processing and fusion, remote control, and communication, with the final intent of achieving a fully integrated and autonomous worldwide maritime transportation system, where a human-less collaborative conflict resolution could potentially retire the COLREGs. However, the maritime sector will first face a transition period where traditional ships will share the seas and interact with heterogeneous MASS with various autonomous capabilities featuring different and probably incompatible communication protocols. In such a scenario, the COLREGs will still play a primary role in helping the collision avoidance systems resolve conflicts and limiting the degrees of freedom. This paper aims to study the interaction among multiple vessels with autonomous collision avoidance capabilities operating in a close navigation scenario. The ships operate according to a COLREG-compliant collision avoidance algorithm. The paper relies on numerical simulation to systematically investigate different scenarios in which autonomous vessels operate and interact in the presence of fixed obstacles. Results are presented and critically discussed.

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Fulbright, Joy M., Wendy McClellan, Gary C. Doolittle, Hope Krebill, Robin Ryan, Kyla Alsman e Becky N. Lowry. "Nurse navigation: The key to a seamless transition." Journal of Clinical Oncology 34, n. 3_suppl (20 gennaio 2016): 84. http://dx.doi.org/10.1200/jco.2016.34.3_suppl.84.

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84 Background: Children's Mercy (CM) established a cancer survivorship clinic that cares for approximately 180 survivors a year. A third of the survivors are 18 years or older requiring transition to adult care. The importance of transitioning childhood cancer survivors from pediatric oncology care to adult primary care has been acknowledged in literature, but obstacles remain. Barriers include patient and provider anxiety, difficulty navigating the complex health care system and lack of knowledge regarding late effects. CM and The University of Kansas Cancer Center (KUCC) collaborated to decrease barriers to transition for childhood cancer survivors. Methods: The work group met for 2 years to develop the clinic at KUCC. Models and delivery of survivorship care, including the breast cancer survivorship clinic at KUCC, were reviewed. A shared nurse navigator was identified as an essential component to a seamless transition. Philanthropic support was obtained and job description was developed. Contracts were negotiated to allow the navigator to be present at both institutions. Results: The Survivorship Transition Clinic (STC) at KUCC launched July 2014, with a navigator supporting patients at CM as they begin their transition. The same navigator then meets with the patient at KUCC STC as they initiate care. The navigator provides treatment summaries, patient education and navigates the referral services for survivors. Since clinic launch, 16 survivors out of 16 have successfully transitioned from pediatric to adult survivorship care. Positive feedback was received from patient satisfaction surveys that were administered. A common theme showed a relief from anxiety due to having a contact person to facilitate communication among providers in a complex healthcare system. Conclusions: The nurse navigator has minimized anxiety about transition for patients and parents as she establishes a relationship with patients at CM, and then is able to provide continuity as they transition to the STC at KUMC. The navigator also improves communication between pediatric providers, adult primary care providers and sub-specialists caring for the patients. Overall, our transition process has been effective and is now serving as a model across both institutions.

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Zhu, Lihua. "Design and Simulation Analysis of Simultaneous Localization and Mapping System for Robot Using Multi Photoelectric Sensors". Journal of Nanoelectronics and Optoelectronics 16, n. 3 (1 marzo 2021): 420–27. http://dx.doi.org/10.1166/jno.2021.2966.

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Robot technology integrates motion control, information fusion and wireless communication technology. Among them, simultaneous localization and mapping (SLAM) technology is the key to realize robot autonomous navigation. In this exploration, multi photoelectric sensors are used for information fusion to solve the nonlinear and uncertain problems of robot navigation system in obstacle avoidance. The acoustic optical sensor and photoelectric sensor are integrated to collect the information of the surrounding environment. The photoelectric encoder of the drive motor is used to control the direct current machine with fuzzy PID closed-loop control. The methods of extended Kalman filter based SLAM (EKF-SLAM) and particle filter based SLAM (PF-SLAM), which are commonly used in navigation problems, are studied and compared. The proposed SLAM system adopts ARM11 high performance processor structure of S3C6410. ARM processor is responsible for task management, input and output, acoustic optical sensor can provide distance and position information, and photoelectric sensor can provide two-dimensional plane information. Their information fusion helps to restore the three-dimensional information of the environment around the robot. In the simulation analysis, the robot moves in a circular way on the horizontal ground. SLAM algorithm based on the information fusion of multi photoelectric sensors can help the robot better perceive the surrounding environment in unknown environment, increase the movement distance and reduce the overall positioning error; the robot can avoid obstacles well in autonomous mode after hardware and algorithm debugging. In the remote control mode, the movement of the robot can be adjusted by controlling the direction.

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