Research on Robot Path Planning Model Based on Improved Cellular Automata

This study develops an improved cellular automaton-based path planning model with multi-objective optimization capabilities to address complex navigation challenges in mobile robotics and autonomous parking systems. The cellular automata model has an advantage in dealing with complex environments, and shows better robustness in such environments. Therefore, in order to solve the problem of robot path planning, this paper makes several improvements to the cellular automata model, so that it can be applied to the field of robot path planning.In this study, the motion range of the robot is abstracted into a two-dimensional space grid, the initial state of the cell is defined according to the parameters of the motion chassis, and a conversion rule based on the improved cell automaton is designed according to the requirements of obstacle avoidance and optimal path, it is iterative to find an efficient and safe path to reach the predetermined target point. In order to accurately evaluate the path quality and numerically analyze the path quality, this paper also designs a path quality evaluation formula to evaluate the feasibility, safety and convenience of the planned path. Compared with the traditional evaluation formula, this paper couples the path quality with the feasibility, safety, and convenience indicators, and the calculated values can reflect the comprehensive quality of the three indicators at the same time. The simulation results show that, compared with the traditional path planning model, the robot path planning model based on the improved cellular automata developed in this paper has significant improvement in three indicators: feasibility, safety and convenience.