Toward asymptotically optimal motion planning for kinodynamic systems using a two-point boundary value problem solver

2015 ◽  
Author(s):  
Christopher Xie ◽  
Jur van den Berg ◽  
Sachin Patil ◽  
Pieter Abbeel
Keyword(s):  
Boundary Value Problem ◽  
Motion Planning ◽  
Boundary Value ◽  
Problem Solver ◽  
Point Boundary ◽  
Optimal Motion ◽  
Asymptotically Optimal ◽  
Optimal Motion Planning

scholarly journals Informed Anytime Fast Marching Tree for Asymptotically-Optimal Motion Planning

2020 ◽  
pp. 1-1
Author(s):  
Jing Xu ◽  
Kechen Song ◽  
Defu Zhang ◽  
Hongwen Dong ◽  
Yunhui Yan ◽  
...  
Keyword(s):  
Motion Planning ◽  
Optimal Motion ◽  
Fast Marching ◽  
Asymptotically Optimal ◽  
Optimal Motion Planning

scholarly journals Iterative methods for efficient sampling-based optimal motion planning of nonlinear systems

2018 ◽  
Vol 28 (1) ◽  
pp. 155-168
Author(s):  
Jung-Su Ha ◽  
Han-Lim Choi ◽  
Jeong Hwan Jeon
Keyword(s):  
Nonlinear Systems ◽  
Boundary Value Problem ◽  
Distance Measure ◽  
Asymptotic Optimality ◽  
Point Boundary ◽  
Optimal Motion ◽  
Tree Construction ◽  
Efficient Sampling ◽  
Optimal Motion Planning ◽  
Problem Solvers

AbstractThis paper extends the RRT* algorithm, a recently developed but widely used sampling based optimal motion planner, in order to effectively handle nonlinear kinodynamic constraints. Nonlinearity in kinodynamic differential constraints often leads to difficulties in choosing an appropriate distance metric and in computing optimized trajectory segments in tree construction. To tackle these two difficulties, this work adopts the affine quadratic regulator-based pseudo-metric as the distance measure and utilizes iterative two-point boundary value problem solvers to compute the optimized segments. The proposed extension then preserves the inherent asymptotic optimality of the RRT* framework, while efficiently handling a variety of kinodynamic constraints. Three numerical case studies validate the applicability of the proposed method.

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