Spark PRM: Using RRTs within PRMs to efficiently explore narrow passages

Shi, Kensen; Denny, Jory; Amato, Nancy M.

doi:10.1109/icra.2014.6907540

Cited by 30 publications

(17 citation statements)

References 26 publications

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“…This approach divides the trajectory into segments around the obstacles. The work Shi et al (2014) proposes a methodology based on RRT that triggers the growth of samples from points in narrow passages until the map is fulfilled.…”

Section: Related Work and Backgroundmentioning

confidence: 99%

Methodology for Autonomous Crossing Narrow Passages Applied on Assistive Mobile Robots

Maciel

Pinto

Júnior

et al. 2019

J Control Autom Electr Syst

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The assistive robotics field works with technologies aimed at assisting people with physical impairments. Simple tasks like passing through doorways can be a significant challenge for motored wheelchairs users. Besides, depending on the disability degree, the task may be impossible to complete without help. Therefore, mobile robotics technologies have been implemented in wheelchairs to give them intelligence, and a supervisory interface inserts the user in the control loop to complete the objectives. Thus, this research proposes an innovative method to assist the user to cross narrow passages automatically. The methodology works in known and unknown environments. Besides, it does not require mapping and global localization algorithms. In this technique, a depth camera recognizes the edges between a narrow path. A Kalman filter method is used to improve the precision of these points even when the passage leaves the camera field of view. Finally, a nonlinear controller performs the narrow passage crossing. This methodology was analyzed using a MATLAB model, Gazebo simulation platform, and a real mobile robot Pioneer-P3DX. The results demonstrated promising applicability. Keywords Narrow passages • Assistive robotics • Mobile robots • Collision avoidance • Intelligent wheelchair 1 Introduction Depending on the disability degree, many people are not able to use both manuals and motorized wheelchairs with an independent movement. For instance, people with quadriplegia or with neuromuscular diseases and older people are unable to use wheelchairs with independence. Therefore, in the last years, researches have been using original mobile robotics technologies for the development of intelligent wheelchairs (IWs) to overcome this issue, such as in Simpson (2005). Different from conventional motorized wheelchairs, the IW has good processing capability, sensors, actuator, and communication interfaces with the user. An intelligent wheelchair is a standard power wheelchair containing a sen

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Section: Related Work and Backgroundmentioning

confidence: 99%

Methodology for Autonomous Crossing Narrow Passages Applied on Assistive Mobile Robots

Maciel

Pinto

Júnior

et al. 2019

J Control Autom Electr Syst

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“…Alternatively, the difficulty of path finding around narrow passages can be mitigated by designing effective local planners. Sampling-based [26], [27] and search-based (e.g., A*like) [13], [28], [29] local planning approaches have been demonstrated to perform better than the standard straight-line planner near narrow passages, but these approaches require storage of path segments joining sample configurations and so cause an increase in memory requirements. This additional memory complexity can be reduced by constraining the search space to a low dimensional subspace and/or limiting the number of vertices used to represent path segments [30].…”

Section: A Motivation and Prior Literaturementioning

confidence: 99%

Sensory steering for sampling-based motion planning

Arslan

Pacelli

Koditschek

2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Sampling-based algorithms offer computationally efficient, practical solutions to the path finding problem in high-dimensional complex configuration spaces by approximately capturing the connectivity of the underlying space through a (dense) collection of sample configurations joined by simple local planners. In this paper, we address a long-standing bottleneck associated with the difficulty of finding paths through narrow passages. Whereas most prior work considers the narrow passage problem as a sampling issue (and the literature abounds with heuristic sampling strategies) very little attention has been paid to the design of new effective local planners. Here, we propose a novel sensory steering algorithm for sampling-based motion planning that can "feel" a configuration space locally and significantly improve the path planning performance near difficult regions such as narrow passages. We provide computational evidence for the effectiveness of the proposed local planner through a variety of simulations which suggest that our proposed sensory steering algorithm outperforms the standard straight-line planner by significantly increasing the connectivity of random motion planning graphs.

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“…e Rapidly-Exploring Random Tree algorithm, which is biased to search and bidirectional expansion, improves the convergence speed and search efficiency but does not overcome the randomness when random trees generate nodes [20,21]. e RRT * algorithm was proposed by Adiyatov and Varol [22].…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Vehicle Path Planning Based on Rapidly-Exploring Random Tree

Shi

et al. 2020

Mathematical Problems in Engineering

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Aiming at the problems of large randomness, slow convergence speed, and deviation of Rapidly-Exploring Random Tree algorithm, a new node is generated by a cyclic alternating iteration search method and a bidirectional random tree search simultaneously. A vehicle steering model is established to increase the vehicle turning angle constraint. The Rapidly-Exploring Random Tree algorithm is improved and optimized. The problems of large randomness, slow convergence speed, and deviation of the Rapidly-Exploring Random Tree algorithm are solved. Node optimization is performed on the generated path, redundant nodes are removed, the length of the path is shortened, and the feasibility of the path is improved. The B-spline curve is used to insert the local end point, and the path is smoothed to make the generated path more in line with the driving conditions of the vehicle. The feasibility of the improved algorithm is verified in different scenarios. MATLAB/CarSim is used for joint simulation. Based on the vehicle model, virtual simulation is carried out to track the planned path, which verifies the correctness of the algorithm.

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Spark PRM: Using RRTs within PRMs to efficiently explore narrow passages

Cited by 30 publications

References 26 publications

Methodology for Autonomous Crossing Narrow Passages Applied on Assistive Mobile Robots

Methodology for Autonomous Crossing Narrow Passages Applied on Assistive Mobile Robots

Sensory steering for sampling-based motion planning

Research on Intelligent Vehicle Path Planning Based on Rapidly-Exploring Random Tree

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