Visual Obstacle Avoidance Trajectory Control of Intelligent Loading and Unloading Robot Arm Based on Hybrid Interpolation Spline

Due to existing methods not fully considering the issues of uneven movement speed, dynamic collision conflicts, and trajectory discontinuity of the robotic arm, the control effect is poor in complex environments, and the safety of intelligent loading and unloading robotic arm loading and unloading operations is poor. To this end, a visual obstacle avoidance trajectory control method for intelligent loading and unloading robotic arms based on mixed interpolation splines is proposed. Firstly, the camera is used to capture environmental images, calculate disparity maps of images at different positions, and perform binary processing on them. Based on this, the contour extraction algorithm is used to obtain the contour and center coordinates of obstacles, completing obstacle localization; Then, an improved TEB-VO algorithm is proposed by combining the time elastic band algorithm with the speed obstacle algorithm. The algorithm is used to control the obstacle avoidance trajectory of the intelligent loading and unloading robot arm, constrain the robot arm’s speed, and avoid collision conflicts. Finally, a mixed interpolation spline is used to optimize the trajectory control, improving the continuity of the trajectory control under the maximum curvature constraint of the path. The experimental results show that the proposed method has high smoothness of obstacle avoidance trajectory, high control efficiency, and strong adaptability.