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

2015 ◽  
Vol 7 (1) ◽  
pp. 106-113
Author(s):  
Hong Liu ◽  
Yan Wang
Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Peng Cai ◽  
Xiaokui Yue ◽  
Hongwen Zhang

Abstract In this paper, we present a novel sampling-based motion planning method in various complex environments, especially with narrow passages. We use online the results of the planner in the ADD-RRT framework to identify the types of the local configuration space based on the principal component analysis (PCA). The identification result is then used to accelerate the expansion similar to RRV around obstacles and through narrow passages. We also propose a modified bridge test to identify the entrance of a narrow passage and boost samples inside it. We have compared our method with known motion planners in several scenarios through simulations. Our method shows the best performance across all the tested planners in the tested scenarios.


Author(s):  
Yu Yan ◽  
Emilie Poirson ◽  
Fouad Bennis

This paper presents a novel interactive motion planning system for assembly/disassembly operations. Our system consists of three layers: interaction layer, learning layer and motion library layer. In interaction layer, user’s manipulation in difficult scenario is liberated by relaxing collision constraints. The resulting path is retracted and connected by random retraction method and BiRRT algorithm. A motion path which successfully passed through the narrow passage or information of geometrical interference in failed case is returned to user. In learning layer, motion primitives corresponding to prior similar scenario are selected by scenario comparison which is based on medial axis, and then transformed to generate new motions. Significant improvement for motion planning of non-convex object in challenging scenarios with narrow passages is obtained by interactive process. The introduction of learning mechanism can reduce global planning time and obtain experiential knowledge.


2006 ◽  
Author(s):  
Jonathan Vaughan ◽  
Steven Jax ◽  
David A. Rosenbaum
Keyword(s):  

2005 ◽  
Author(s):  
John Neumann ◽  
Jennifer M. Ross ◽  
Peter Terrence ◽  
Mustapha Mouloua

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