An Efficient RRT-Based Framework for Planning Short and Smooth Wheeled Robot Motion under Kinodynamic Constraints

Document Type

Article

Publication Date

4-1-2021

Abstract

This article presents a framework that extends a rapidly exploring random tree (RRT) algorithm to plan the motion for a wheeled robot under kinodynamic constraints. Unlike previous RRT-based path planning algorithms that apply complex steer functions during a path sampling phase, this framework uses a straight line to connect a pair of sampled waypoints such that an obstacle-free path can be quickly found. This path is further pruned by the short-cutting algorithm. Under the kinodynamic constraints, we propose a motion-control law that is guided by a pose-based steer function for the robot to reach its destination in a short time. A path deformation strategy is presented that shifts the waypoint away from the collision point such that the trajectory can be generated without any collision. Simulation results demonstrate that the proposed framework needs less computation to generate a smoother trajectory with shorter length than its peers, and experimental results show that simulated trajectories of our controller are very close to real ones and the performance is better than that of a prior pose-based controller.

Identifier

85097932551 (Scopus)

Publication Title

IEEE Transactions on Industrial Electronics

External Full Text Location

https://doi.org/10.1109/TIE.2020.2978701

e-ISSN

15579948

ISSN

02780046

First Page

3292

Last Page

3302

Issue

4

Volume

68

Grant

51575034

Fund Ref

National Natural Science Foundation of China

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