Application of Improved Butterfly Optimization Algorithm in Mobile Robot Path Planning

• DOI: 10.3390/electronics12163424
• Publication Date: 2023-08-14T14:28:13Z
• Authors: Rongjie Zhai; Ping Xiao; Da Shu; Yongjiu Sun; Min Jiang
• Keywords: Yen's algorithm; Grid reference

An improved butterfly optimization algorithm (IBOA) is proposed to overcome the disadvantages, including slow convergence, generation of local optimum solutions, and deadlock phenomenon, in path planning mobile robots. A path-planning grid model established based on an obstacle model. First, population diversity by introducing kent mapping during position renewal normal (BOA) enhance global search ability population. Second, adaptive weight coefficient introduced process each increase convergence speed accuracy. opposition-based learning strategy convex lens imaging help jump out optimum. Finally, a mutation solve problem. On this basis, two simplification strategies are make up for shortcomings paths maps. The shortest lengths solved IBOA, BOA, GA 20 × map 30.97, 31.799, respectively. numbers iterations searched 14, 24, 38 that order. BOA 40 63.84, 65.60, 65.84, number 32, 40, 46, Simulation results show IBOA has strong robot problems can effectively reduce length optimal problem maps simplified 30.2914 61.03,