SUMMARYMany applications require unmanned ground vehicles (UGVs) to travel at high speeds on sloped, natural terrain. In this paper, a potential field-based method is proposed for UGV navigation in such scenarios. In the proposed approach, a potential field is generated in the two-dimensional “trajectory space” of the UGV path curvature and longitudinal velocity. In contrast to traditional potential field methods, dynamic constraints and the effect of changing terrain conditions can be easily expressed in the proposed framework. A maneuver is chosen within a set of performance bounds, based on the local potential field gradient. It is shown that the proposed method is subject to local maxima problems, rather than local minima. A simple randomization technique is proposed to address this problem. Simulation and experimental results show that the proposed method can successfully navigate a small UGV between predefined waypoints at speeds up to 7.0 m/s, while avoiding static hazards. Further, vehicle curvature and velocity are controlled during vehicle motion to avoid rollover and excessive side slip. The method is computationally efficient, and thus suitable for onboard real-time implementation.
Artificial potential field algorithm for path control of unmanned ground vehicles formation in highway
