Multipoint potential field method for path planning of autonomous underwater vehicles in 3D space
A multipoint potential field method (MPPF) for path planning of autonomous underwater vehicles (AUV) in 3D space is presented in this paper. The algorithm is developed based on potential field method by incorporating a directed search method for sampling the potential field. In this approach, the analytical gradient of the total potential function is not computed, as it is not essentially required for moving the vehicle to the next position. Rather, a hemispherical region in the direction of motion around the AUVs bow is discretized into equiangular points with center as the current position. By determining the point at which the minimum potential exists, the vehicle can be moved towards that point in 3D space. This method is very simple and applicable for real-time implementation. The problem of local minima is also analyzed and found that the local minima in 2D space can be easily overcome with the MPPF. A simple strategy to avoid the local minima in 3D space is also proposed. The proposed method reduces the burden of fine-tuning the positive scaling factors of potential functions to avoid local minimum. The algorithm development and the simulation results are presented.
potential field path planning auv local minimum obstacle avoidance