A path planning method for mobile robot based on artificial potential field;

Navigation of mobile robot using improved artificial potential field method;

Research on Reinforcement Learning Problem Based on Artificial Potential Field;

The artificial potential field method is widely used for mobile robot path planning due to its simplicity and mathematical analysis,However,most reaserches have been focused on solving the path planning in a stationary environment where both targets and obstacles are stationary.

Secondly, this thesis introduces some popular methods for path planning, such as the global path planning methods, including artificial potential field, topology, visual graph and free-space method; including the local path planning methods, neural network, fuzzy logic and genetic algorithm and analyzes the advantages and weakpoints of these meth

On the basis of building forward looking sonar view model and artificial potential model,decision control of AUV is made,objects are searched through grads approach,a collision free path is planed.

The reinforcement learning is adopted to control and decision for AUV,and Q-learning,BP neural net,artificial potential is integrated to avoidance planning for AUV.

The reinforcement learning is adopted to control and decision for Autonomous Underwater Vehicles (AUV), and Q- learning , BP neural net, artificial potential is integrated to local plan for AUV.

The time varying potential field algorithm is presented, with some improvements to model the environment and avoid obstacles.

Research on artificial potential field for robot soccer path planning;

A path Planning of mobile robot based on improved artificial potential field method

Path planning of cutting pipe fittings based on artificial potential field