Redundant Robot

Redundant robots, possessing more degrees of freedom than necessary for a given task, are studied to improve dexterity, robustness, and efficiency in various applications. Current research focuses on developing efficient trajectory optimization methods, often employing techniques like dynamic programming and GPU-accelerated distance field computations for real-time collision avoidance and multi-task execution with task prioritization. These advancements address challenges in inverse kinematics, path planning, and constraint handling, leading to improved control algorithms and enabling more complex and adaptable robot behaviors in manufacturing, service robotics, and other fields.