Approaches for heuristically biasing RRT growth

Urmson, Chris; Simmons, Reid

doi:10.1109/iros.2003.1248805

Cited by 252 publications

(155 citation statements)

References 7 publications

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“…To avoid this problem, two modifications can be introduced in BestNeighbor: (1) A node is no longer selected after its expansion fails a given number of consecutive times l. (2) q near is selected at random among the k nearest neighbors 3 . The efficiency of these two modifications has been shown in related works [18], [19], [20]. One can also choose a more or less greedy strategy for the expansion procedure (function Expand in Algorithm 1).…”

Section: The Basic Rrt Algorithmmentioning

confidence: 99%

Disassembly Path Planning for Complex Articulated Objects

Cortés¹,

Siméon²

2008

IEEE Trans. Robot.

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Abstract:Sampling-based path planning algorithms are powerful tools for computing constrained disassembly motions. This paper presents a variant of the RRT algorithm particularly devised for the disassembly of objects with articulated parts. Configuration parameters generally play two different roles in this type of problems: some of them are essential for the disassembly task, while others only need to move if they hinder the progress of the disassembly process. The proposed method is based on such a partition of the configuration parameters. Results show a remarkable performance improvement compared to standard path planning techniques. The paper also shows practical applications of the presented algorithm in robotics and structural bioinformatics. Keywords:Path planning algorithms, Disassembly paths, Articulated mechanisms, Robotic manipulation, Molecular interactions. Abstract-Sampling-based path planning algorithms are powerful tools for computing constrained disassembly motions. This paper presents a variant of the RRT algorithm particularly devised for the disassembly of objects with articulated parts. Configuration parameters generally play two different roles in this type of problems: some of them are essential for the disassembly task, while others only need to move if they hinder the progress of the disassembly process. The proposed method is based on such a partition of the configuration parameters. Results show a remarkable performance improvement compared to standard path planning techniques. The paper also shows practical applications of the presented algorithm in robotics and structural bioinformatics. Submitted to IEEE Transactions of Robotics as Short Paper

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Section: The Basic Rrt Algorithmmentioning

confidence: 99%

Disassembly Path Planning for Complex Articulated Objects

Cortés¹,

Siméon²

2008

IEEE Trans. Robot.

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“…RRTs have been used in several applications, and many variants have been developed [18,24,26,37,38,42,47,57,65,85,88,87,92,113,120,121,156,157,162,168,169]. Originally, they were developed for planning under differential constraints, but most of their applications to date have been for ordinary motion planning.…”

Section: Further Readingmentioning

confidence: 99%

Combinatorial Motion Planning

LaValle

2006

Planning Algorithms

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“…But the above and basic RRTs can not effectively control the path quality. Urmson Simmons put forward a RRT algorithm based-on heuristic searching (h-RRT) [7], which is to inspire the spanning tree with growing to the blank area which can produce optimal path. The evaluation function of path cost is establishment based on the size of Voronoi region.…”

Section: Introductionmentioning

confidence: 99%

Lift Path Planning for Telescopic Crane Based-on Improved hRRT

Lin¹,

Wang²,

Wu³

et al. 2013

IJCTE

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Abstract-The hRRT algorithms based on heuristics can solve many path planning problems, but its efficiency can still be improved. We deeply analyze the details of hRRT, and enhance it by using bi-directional tree and adopting kd-tree as secondary data structure to select nearest neighbors. At last, the improved hRRT is used for lift path planning for telescopic crane, and the efficiency of the improved hRRT is verified. The result of the experiment shows that the enhanced hRRT can dramatically shorten the plan time without reducing the quality of path.Index Terms-Rapidly-exploring random tree, hRRT, path planning, crane lifting.

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Approaches for heuristically biasing RRT growth

Abstract: This paper presents several modifications to the basic rapidly-exploring random tree (RRT)

Cited by 252 publications

References 7 publications

Disassembly Path Planning for Complex Articulated Objects

Disassembly Path Planning for Complex Articulated Objects

Combinatorial Motion Planning

Lift Path Planning for Telescopic Crane Based-on Improved hRRT

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