In this work, we investigate a form of dynamic contact-rich locomotion in which a robot pushes off from obstacles in order to move through its environment. We present a reflex-based approach that switches between optimized hand-crafted reflex controllers and produces smooth and predictable motions. In contrast to previous work, our approach does not rely on periodic movements, complex models of robot and contact dynamics, or extensive hand tuning. We demonstrate the effectiveness of our approach and evaluate its performance compared to a standard model-free RL algorithm. We identify continuous clusters of similar behaviours, which allows us to successfully transfer different push-off motions directly from simulation to a physical robot without further retraining.

We present a novel method for the direct transfer of grasps and manipulations between objects and hands through utilization of contact areas. Our method fully preserves contact shapes, and in contrast to existing techniques, is not dependent on grasp families, requires no model training or grasp sampling, makes no assumptions about manipulator morphology or kinematics, and allows user control over both transfer parameters and solution optimization. Despite these accommodations, we show that our method is capable of synthesizing kinematically-feasible whole hand poses in seconds even for poor initializations or hard-to-reach contacts. We additionally highlight the method's benefits in both response to design alterations as well as fast approximation over in-hand manipulation sequences. Finally, we demonstrate a solution generated by our method on a physical, custom-designed prosthetic hand.