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Grasp planning and motion synthesis for dexterous manipulation tasks are traditionally done given a pre-existing kinematic model for the robotic hand. In this paper, we introduce a framework for automatically designing hand topologies best suited for manipulation tasks given high-level objectives as input. Our pipeline is capable of building custom hand designs around specific manipulation tasks based on high-level user input. Our framework comprises of a sequence of trajectory optimizations chained together to translate a sequence of objective poses into an optimized hand mechanism along with a physically feasible motion plan involving both the constructed hand and the object. We demonstrate the feasibility of this approach by synthesizing a series of hand designs optimized to perform specified in-hand manipulation tasks of varying difficulty. We extend our original pipeline 32 to accommodate the construction of hands suitable for multiple distinct manipulation tasks as well as provide an in depth discussion of the effects of each non-trivial optimization term. 

There has been great progress in soft robot design, manufacture, and control in recent years, and soft robots are a tool of choice for safe and robust handling of objects in conditions of uncertainty. Still, dexterous in-hand manipulation using soft robots remains a challenge. This paper introduces foam robot hands actuated by tendons sewn through a fabric glove. The flexibility of tendon actuation allows for high competence in utilizing deformation for robust in-hand manipulation. We discuss manufacturing, control, and design optimization for foam robots and demonstrate robust grasping and in-hand manipulation on a variety of different physical hand prototypes. 

Abstract — We present a class of tendon-actuated soft robots, which promise to be low-cost and accessible to non-experts. The fabrication techniques we introduce are largely based on traditional techniques for fabricating plush toys, and so we term the robots created using our approach “plush robots.” A plush robot moves by driving internal winches that pull in (or let out) tendons routed through its skin. We provide a forward simulation model for predicting a plush robot’s deformation behavior given some contractions of its internal winches. We also leverage this forward model for use in an interactive control scheme, in which the user provides a target pose for the robot, and optimal contractions of the robot’s winches are automatically computed in real-time. We fabricate two examples to demonstrate the use of our system, and also discuss the design challenges inherent to plush robots.