Path Planning for Amphibious Robots with Energy Constrained

Qijun Li, Xinde Li, Huitong Zhang, Qiurong Sun, Zhuoran Zhu, Yuxin Liu, Chenyang Zhao, Heqing Li

Abstract: Aiming at the problem of path planning for land-air amphibious robot in dense urban environment, an improved A * algorithm (IA *-AGPF) integrating artificial gravitational potential field is proposed. By expanding the spatial motion matrix of the A * algorithm under the minimum energy constraint, and introducing the artificial gravitational potential field, we enhance the perception ability of the land-air amphibious UAV to the ground path. Furthermore, we simulate small-scale urban roadway scenarios and introduce a variety of urban complex obstacles to verify the effectiveness of the IA *-AGPF algorithm. Simulation experiment results show that the proposed IA *-AGPF algorithm performs better than the traditional ant colony, A * and RRT algorithms when considering the minimum energy constraints.