Path Planning Algorithm Based on the Dynamic Restriction of Ellipse and Immune Mechanism

This study proposes an algorithm based on the dynamic restriction of an ellipse and immune mechanism to solve robot path planning problems. First, the initial antibody population is generated in the omnidirectional space by the vaccine-inspired factors. Next, a node storage structure is introduced as the primary computing unit to avoid repeated calculation of local path information.Node mutation is used to update node information. Then, an ellipse search area is then constructed under the confidence level of 100% by the path value, and the ellipse search area is dynamically reduced without affecting the optimal path solution. Invalid nodes are deleted continuously through the node deletion under two-level restrictions, which improves the search efficiency. Finally, the proposed algorithm was compared with other algorithms, where the simulation results verified the certainty and effectiveness of the algorithm. The search time is reduced by 77.24%, and the number of nodes is reduced by 55.54%.