Research on Path Planning of Manipulator Based on the Improved RRT-Connect Algorithm

With the development of intelligent manufacturing, manipulators are being increasingly used in the tobacco industry. Path planning of manipulators is a key technology for achieving high-efficiency production. The traditional RRT-Connect algorithm has several problems, such as low efficiency, high randomness, long search time, excessive number of iterations and nodes, and long path planning. An improved RRT-Connect path-planning algorithm was proposed. First, two strategies, namely constraining the sampling area and target-oriented growth, are proposed to reduce the number of sampling times and randomness of the algorithm and shorten the planning time. Second, key points are obtained through path pruning to shorten the path length. Finally, a spline interpolation method is used to smooth the path and improve the operational stability of the manipulator. Through MATLAB simulation verification, the improved RRT-Connect algorithm can significantly reduce the number of sampling nodes, shorten the planning time, reduce randomness, and generate a continuous and smooth trajectory during path planning.