Enhancing Motion Planning for Industrial Robots Using Hybrid Methods and Quaternion Representation

Abstract

This research addresses the limitations of relying on single trajectory types,  which often resulting jerky and inefficient movements, especially in complex scenarios . This research present an enhanced motion planning methodology for industrial robots that integrates hybrid trajectory methods with quaternion representation . Our approach combines Linear-SLERP, B-Spline, and Bézier  curves to achieve smooth, adaptive  and efficient path planning suitable for diverse industrial environments. By leveraging the strengths of the trajectory method the hybrid approach ensures continuous and stable robot manipulations. Quaternion representation is utilized to avoid gimbal lock and to provide a robust orientation framework  enhancing the motion smoothness of industrial robots . The research implemented proposed method using CoppeliaSim with a 7-DoF Franka Emika Panda robotic arm performing a standard pick-and-place task. The results demonstrate that the proposed hybrid method significantly reduces acceleration and jerk compared to traditional trajectory methods thereby minimizing mechanical stress and enhancing overall motion efficiency . This research offers a novel and effective solution for complex robotic applications  ensuring precise and stable operations across various industrial settings.

DOI: 10.61416/ceai.v27i1.9217