Smooth Path Planning for Continuum Arms

Continuum arms, with their mix of compliance, payload, safety, and manipulability, are perfectly suited to serve as co-robots, and their applications range from industry and manufacturing to human healthcare. Their hyper-redundancy serves as their most significant challenge for path planning and path planning approaches commonly used with rigid-link robots, such as inverse kinematics, that fail to provide reliable trajectories for continuum arms. We propose an Inverse Kinematics-based approach to address the limitations of previously-proposed Kinematics-based approaches. Using this new approach, we are able to efficiently generate very rich sets of configurations, which, in turn, lead to smooth path planning for such continuum manipulators. To validate the smoothness of the paths generated by our approach, we apply dynamics constraints to the generated trajectories. We show that, when tracked by a controller, the paths that are generated using the proposed approach are much smoother than previously-proposed Kinematics-based approaches: The proposed approach allows the continuum arm to traverse the trajectories very accurately and in time less than half of that taken by previous (reliable) path planning approaches.