A "capacitor" bridge builder based safe path planner for difficult regions identification in changing environments

Liu, Hong; Zhang, Tianwei; Wang, Chuangqi

doi:10.1109/iros.2012.6386059

Cited by 8 publications

(5 citation statements)

References 17 publications

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“…Safe motion planning has been studied in several works and is important to guarantee the robot's security and reduce total planning cost. As a variant of DBB, Capacitor Bridge Builder (CBB) is proposed to identify difficult but relatively safe regions in changing environments [14]. Nevertheless, CBB does not pay attention to the variation trend of narrow passage in the C-space, which is crucial for the security of planning.…”

Section: Related Workmentioning

confidence: 99%

“…Points in P record the fundamental structure of C-space. In order to describe the validity toggle of points in P, we follow a similar definition of P + and Pto that introduced in [14]: p! P + " #p!…”

Section: Hierarchical Sampling Strategymentioning

confidence: 99%

“…Dynamic Roadmaps (DRMs) [11,12] are put forward to cope with motion planning problems in changing environments. However, they are still confronted with difficulties from narrow passages of C-free and only a few researches have paid attention to this work [13,14]. In changing environments, considering the indeterminacy of the variation trend of narrow passages, it is hard for the planner to consciously seek out a safe path passing through narrow passages which keep narrowing down.…”

Section: Introductionmentioning

confidence: 99%

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Narrow Passage Watcher for Safe Motion Planning by Using Motion Trend Analysis of C-Obstacles

Liu¹,

Wang²

2015

TOAUTOCJ

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Finding safe paths for robots in changing environments is a significant issue for motion planning. However, it could be fairly difficult when there are narrow passages in the configuration space. Solutions to this problem can be applicable to not only mobile robots but also other domains such as computer animation and computational biology. This paper presents a novel method called Narrow Passage Watcher (NPW) to cope with narrow passage issues in changing environments. It approximately predicts the variation trend of narrow passages and analyzes their security and thus guides to safe path planning. Meanwhile, a supporting hybrid boost strategy is presented to increase the sampling density inside narrow passages with different variation trend. Compared with existing work, the predictive mechanism provided by NPW gives the planner foresight so that it can find safer paths in changing environments with a higher success rate. Experiments conducted with a dual-manipulator system with 12 DOFs show that NPW can reduce the number of replanning times and total planning time remarkably as well as improving the success rate of path planning.

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Section: Related Workmentioning

confidence: 99%

Section: Hierarchical Sampling Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Narrow Passage Watcher for Safe Motion Planning by Using Motion Trend Analysis of C-Obstacles

Liu¹,

Wang²

2015

TOAUTOCJ

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“…In [28], sampled points using methods from [26] are used with RRT-Connect [29]. In [30], narrow passage samples are generated by building capacitor bridges between positive and negative toggled points in C-space by flagging boundaries of moving obstacles. In [31], fixed length line segments are uniformly distributed in C-space and their intersection points with C-obstacle surfaces as retained as roadmap nodes.…”

Section: Introductionmentioning

confidence: 99%

A Levy Flight based Narrow Passage Sampling Method for Probabilistic Roadmap Planners

Shukla¹,

Kumar²,

Bera³

et al. 2021

Preprint

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Sampling based probabilistic roadmap planners (PRM) have been successful in motion planning of robots with higher degrees of freedom, but may fail to capture the connectivity of the configuration space in scenarios with a critical narrow passage. In this paper, we show a novel technique based on Lévy Flights to generate key samples in the narrow regions of configuration space, which, when combined with a PRM, improves the completeness of the planner. The technique substantially improves sample quality at the expense of a minimal additional computation, when compared with pure random walk based methods, however, still outperforms state of the art random bridge building method, in terms of number of collision calls, computational overhead and sample quality. The method is robust to the changes in the parameters related to the structure of the narrow passage, thus giving an additional generality. A number of 2D & 3D motion planning simulations are presented which shows the effectiveness of the method.

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“…Recently, [15,16,17] followed the idea that pays attention to the information about obstacles, also biasing the sampling to the difficult region [18,19]. However, all these methods have great computational cost in return and may get a slower result even to a basic RRT method when difficult regions do not exist in the free space.…”

Section: Introductionmentioning

confidence: 99%

Obstacle guided RRT path planner with region classification for changing environments

Liu

Rao

Xiao

2013

2013 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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The Rapidly-exploring Random Tree (RRT) has been widely used to solve path planning problems and well suited to lots of problem domains for its probabilistically complete. However, it is not so rapid in changing environments, troubled with moving obstacles and difficult regions. In this paper, a variant of RRT is proposed which is called obstacle guided RRT (OG-RRT), aiming to plan a path in changing environments efficiently. By preserving a group of invalid configurations blocked by obstacles, an entropy value is introduced to label every state in the tree with region classification information. Then a differentiation strategy is adopted to the framework for extending. Finally, with recording the change between invalid and valid nodes, a fuzzy estimation for obstacles' movements and an opportunistic strategy for reusing information from previous queries will be used to replan a solution fast. In plentiful experiments, OG-RRT is very effective in changing environment.

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A "capacitor" bridge builder based safe path planner for difficult regions identification in changing environments

Cited by 8 publications

References 17 publications

Narrow Passage Watcher for Safe Motion Planning by Using Motion Trend Analysis of C-Obstacles

Narrow Passage Watcher for Safe Motion Planning by Using Motion Trend Analysis of C-Obstacles

A Levy Flight based Narrow Passage Sampling Method for Probabilistic Roadmap Planners

Obstacle guided RRT path planner with region classification for changing environments

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