Kinematic Analysis and Trajectory Planning for Low-Degree-of-Freedom Robotic Manipulators

This paper zeroes in on the four-degree-of-freedom manipulator, subjecting it to meticulous kinematic analysis and optimal trajectory planning to bolster its operational efficiency and stability. The study employs the quintic B-spline curve interpolation algorithm to guarantee seamless and stable trajectory progression. Furthermore, we introduce an advanced particle swarm optimization (PSO) algorithm, infused with a random disturbance factor and a fuzzy adaptive inertia weight strategy, thereby elevating the precision and performance of the PSO methodology. The experimental outcomes validate the accuracy of the manipulator's inverse kinematics calculations, the robustness of the trajectory planning technique, and the planned trajectory's fluidity, coherence, and absence of sudden alterations. These advancements substantially reinforce the robot arm's working capacity and operational stability, furnishing a solid theoretical and empirical foundation for its optimal performance across diverse application contexts.