Research on sensor obstacle avoidance for intelligent connected retail vehicle

The obstacle avoidance sensing application of intelligent connected retail vehicle is one of the current research hotspots of unmanned retail vehicle. This paper studies the obstacle avoidance sensing application of intelligent connected retail vehicle, compares the classic ant colony obstacle avoidance algorithm and Bessel curve obstacle avoidance algorithm, proposes an optimized fusion obstacle avoidance algorithm, determines the starting node and target node, deploys m ants, completes the initial configuration of pheromone distribution, and then iterates. The distance between each point and obstacle on the four Bessel curves of planning and construction meets or exceeds the safety threshold of obstacle avoidance. If the number of quad - Bezier curves screened out according to the conditions exceeds one, it is necessary to further carry out the comparison of path lengths, and choose the shortest one as the selection object. A prototype obstacle avoidance system is designed, which integrates a variety of sensors, can monitor the environment around the vehicle in real time, and take the corresponding obstacle avoidance measures. Through a series of rigorous experiments and verification steps, the effectiveness and scientificity of the algorithm and system proposed in this paper have been confirmed. The experimental results show that the system can detect and avoid obstacles accurately, and improve the safety and stability of the vehicle.