The goal of this work is to develop a soft-robotic manipulation system that is capable of autonomous, dynamic, and safe interactions with humans and its environment. We provide a computational approach to whole arm planning for a soft planar manipulator that advances the arm’s end effector pose in task space while simultaneously considering the arm’s entire envelope in proximity to a confined environment. Further, we develop soft planar grasping manipulators capable of grasp-and-place operations by encapsulation with uncertainty in the position and shape of the object. We also develop a dynamic model for a multi-body fluidic elastomer manipulator that is composed entirely from soft rubber and subject to the self-loading effects of gravity. Then, we present a strategy for independently identifying all of the unknown components of the system. Using our model and trajectory-optimization techniques we find locally-optimal open-loop policies that allow the system to perform dynamic maneuvers. By studying extremely soft robots, we can begin to solve hard problems inhibiting the mainstream use of soft machines.
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