A framework for trajectory optimization of an industrial KUKA robot

Le résumé fourni par la source

The paper presents a trajectory planning and execution framework for a 6-DOF KUKA robotic arm operating in environments with obstacles. The method combines trapezoidal velocity profiles and high-order polynomial trajectories to compute smooth, collision-free paths. Developed in MATLAB Simulink, the simulation framework supports modular, real-time analysis of robotic motion. Forward and inverse kinematics are used to ensure feasible joint and end-effector movements. Simulation results show that hybrid trajectory planning improves motion smoothness, reduces mechanical stress, and lowers collision risks compared to singular approaches. This contributes to more efficient and reliable automation, particularly in applications like precision assembly, automated manufacturing, and service robotics. The study highlights the advantages of integrating multiple planning techniques to optimize robot performance in cluttered or dynamic workspaces. By offering a flexible and executable planning system, the framework enhances robotic motion efficiency, safety, and adaptability in complex industrial environments.

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