A Multi-Operator Based Simulated Annealing Approach for Robot Navigation in Uncertain Environments

摘要

Optimization methods such as simulated annealing (SA) and genetic algorithm (GA) are used for solving optimization problems. However, the computational processing time is crucial for the real-time applications such as mobile robots. A multi-operator based SA approach incorporating with additional four mathematical operators that can find the optimal path for robots in dynamic environments is proposed in this paper. It requires less computation times while giving better trade-offs among simplicity, far-field accuracy, and computational cost. The contributions of the work include the implementing of the simulated annealing algorithm for robot path planning in dynamic environments, and the enhanced new path planner for improving the efficiency of the path planning algorithm. The simulation results are compared with the previous published classic SA approach and the GA approach. The multi-operator based SA (MSA) approach is demonstrated through case studies not only to be effective in obtaining the optimal solution but also to be more efficient in both off-line and on-line processing for robot dynamic path planning. Keywords: Optimization, MSA, SA, GA, Dynamic Environments