There are many situations for which an unmanned ground vehicle has to work with only partial observability of the environment. Therefore, a feasible nonholonomic obstacle avoidance and target tracking action must be generated immediately based on the real-time perceptual information. This paper presents a robust approach to integrating VPH+ (enhanced vector polar histogram) and MPC (model predictive control). VPH+ is applied to calculate the desired direction for its environment perception ability and computational efficiency, while MPC is explored to perform a constrained model-predictive trajectory generation. This approach can be implemented in a reactive controller. Simulation experiments are performed in VREP to validate the proposed approach.
@article{arxiv.1805.08089,
title = {VPH+ and MPC Combined Collision Avoidance for Unmanned Ground Vehicle in Unknown Environment},
author = {Kai Liu and Jianwei Gong and Huiyan Chen},
journal= {arXiv preprint arXiv:1805.08089},
year = {2018}
}