Optimum kinematic – dynamic performance of the reconfigurable delta robot through genetic algorithm optimization

Delta robots play a critical role in high-speed industrial applications due to their parallel kinematic structure, which provides superior precision, agility, and efficiency. This study presents a reconfigurable Delta robot with a novel structural adaptation mechanism, allowing geometric modifications to optimize its kinematic and dynamic performance. The research systematically derives the robot’s kinematic and dynamic equations, examines the impact of altering the structure of its chains, and applies genetic algorithm optimization to enhance its overall functionality. The influence of varying arm lengths, chain structures, and joint configurations is analyzed to determine their effects on workspace, actuator torque requirements, and operational stability. The findings indicate that optimized chain configurations improve workspace utilization by up to 15 %, reduce actuator torque by 12 %, and enhance end-effector speed by 8 %. By integrating structural adaptability and optimization techniques, this study demonstrates that the reconfigurable Delta robot achieves a superior balance between precision, speed, and energy efficiency. These advancements make it a promising solution for next-generation high-speed robotic applications in industries such as packaging, assembly, and medical automation.