DocumentCode :
138067
Title :
Sampling-based trajectory imitation in constrained environments using Laplacian-RRT
Author :
Nierhoff, Thomas ; Hirche, Sandra ; Nakamura, Yoshihiko
Author_Institution :
Inst. of Autom. Control Eng., Tech. Univ. Munchen, München, Germany
fYear :
2014
fDate :
14-18 Sept. 2014
Firstpage :
3012
Lastpage :
3018
Abstract :
This paper presents an incremental sampling-based approach for trajectory imitation in cluttered environments using the RRT* algorithm. Inspired by the discrete Laplace-Beltrami operator the underlying distance metric is based upon the difference from a reference trajectory through a quadratic distance term incorporating velocity and acceleration deviations along the trajectory. Mathematically-backed approximations in combination with a task-space bias make it possible to use standard nearest neighbor methods in task space when expanding the RRT*-tree. It is shown that metric-consistent biases considerably increase the convergence speed. The proposed approach is validated in simulations in a 2D environment and in experiments using a HRP-4 humanoid robot.
Keywords :
approximation theory; humanoid robots; mathematical operators; random processes; sampling methods; trees (mathematics); 2D environment; HRP-4 humanoid robot; Laplacian-RRT; RRT* algorithm; RRT*-tree; constrained environments; convergence speed; discrete Laplace-Beltrami operator; distance metric; incremental sampling-based trajectory imitation; mathematically-backed approximations; metric-consistent biases; standard nearest neighbor methods; Acceleration; Approximation algorithms; Extraterrestrial measurements; Indexes; Trajectory; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on
Conference_Location :
Chicago, IL
Type :
conf
DOI :
10.1109/IROS.2014.6942978
Filename :
6942978
Link To Document :
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