A Path Planning Method Based on Improved Beetle Antennae Search Algorithm for Intelligent Agent
Junjie Ma, Wenbo Zhang, Dong-Sheng Guo, Shan Xue, Zehua Jia, Shuai Li · 2024
The traditional Beetle Antennae Search (BAS) algorithm exhibits strong randomness in intelligent agent path planning, resulting in issues such as low search efficiency and poor path practicability. To address these issues, a path planning method based on Improved Beetle Antennae Search (IBAS) algorithm for intelligent agent is proposed. The method constrains the search direction of the beetle, reducing the randomness of the search. The obstacle expansion strategy is employed, which not only simplifies the difficulty of obstacle processing but also improves path security. In addition, the generated path is optimized by eliminating redundant nodes and oscillating nodes, significantly enhancing the practicability of the path. The results of the algorithm simulation experiments fully demonstrate that the IBAS algorithm exhibits superior optimization speed, shorter path length, and better path practicability while effectively achieving obstacle avoidance.