A Generic Trajectory Planning Method for Constrained All-Wheel-Steering Robots
Ren Xin, Hongji Liu, Yingbing Chen, Jie Cheng, Sheng Wang, Jun Ma, Ming Liu
Abstract
This paper presents a generic trajectory planning method for wheeled robots with fixed steering axes while the steering angle of each wheel is constrained. In the existing literatures, All-Wheel-Steering (AWS) robots, incorporating modes such as rotation-free translation maneuvers, in-situ rotational maneuvers, and proportional steering, exhibit inefficient performance due to time-consuming mode switches. This inefficiency arises from wheel rotation constraints and inter-wheel cooperation requirements. The direct application of a holonomic moving strategy can lead to significant slip angles or even structural failure. Additionally, the limited steering range of AWS wheeled robots exacerbates non-linearity characteristics, thereby complicating control processes. To address these challenges, we developed a novel planning method termed Constrained AWS (C-AWS), which integrates second-order discrete search with predictive control techniques. Experimental results demonstrate that our method adeptly generates feasible and smooth trajectories for C-AWS while adhering to steering angle constraints. Code and video can be found at https://github.com/Rex-sys-hk/AWSPlanning.
BibTeX
@inproceedings{iros2024_agenerictrajecto,
title = {A Generic Trajectory Planning Method for Constrained All-Wheel-Steering Robots},
author = {Ren Xin and Hongji Liu and Yingbing Chen and Jie Cheng and Sheng Wang and Jun Ma and Ming Liu},
booktitle = {IROS 2024},
year = {2024}
}