Trajectory Optimization for Thermally-Actuated Soft Planar Robot Limbs
This work addresses motion planning for soft robots, a domain-specific challenge, but is incremental as it builds on existing optimization techniques applied to a new actuator type.
The authors tackled the problem of generating complex motions for thermally-actuated soft robotic manipulators by developing a trajectory optimization method based on a simplified dynamics model, and validated it with hardware experiments showing promise for open-loop motion generation.
Practical use of robotic manipulators made from soft materials requires generating and executing complex motions. We present the first approach for generating trajectories of a thermally-actuated soft robotic manipulator. Based on simplified approximations of the soft arm and its antagonistic shape-memory alloy actuator coils, we justify a dynamics model of a discretized rigid manipulator with joint torques proportional to wire temperature. Then, we propose a method to calibrate this model from experimental data and demonstrate that the simulation aligns well with a hardware test. Finally, we use a direct collocation optimization with the robot's nonlinear dynamics to generate feasible state-input trajectories from a desired reference. Three experiments validate our approach for a single-segment robot in hardware: first using a hand-derived reference trajectory, then with two teach-and-repeat tests. The results show promise for both open-loop motion generation as well as for future applications with feedback.