Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Nonholonomic Motion Planning
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
Autonomous Robots
An evolutionary method for active learning of mobile robot path planning
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
An analytic approach to moving obstacle avoidance using an artificial potential field
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 2 - Volume 2
Mobile Robot Global Path Planning Based on Improved Augment Ant Colony Algorithm
WGEC '08 Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing
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Traditional APF-based mobile robot path planning approaches posses an inherent problem which is the formation of local minimum that probably prevent robot from arriving at the target. In view of those considerations, an improved potential field function is proposed to settle this problem. The new method includes an improved attractive potential function and an improved repulsive potential function. The attractive potential function takes into account the minimum separation between robot and obstacles, while the repulsive potential function takes into account the relative position between robot and the target. As a result, the target is ensured as the global minimum in working space. Simulation experiments are performed and the results demonstrate the effectiveness of the improved method.