Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
The Navlab system for mobile robot navigation
The Navlab system for mobile robot navigation
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
Autonomous Robots
Robot path planning and obstacle avoidance by means of potential function method
Robot path planning and obstacle avoidance by means of potential function method
Mobile Robots in Rough Terrain: Estimation, Motion Planning, and Control with Application to Planetary Rovers
A convergent dynamic window approach to obstacle avoidance
IEEE Transactions on Robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Many 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.