Soft Pneumatic Actuator skin (SPA-skin) is a novel concept of ultra-thin (<; 1 mm) sensor embedded actuators with distributed actuation points that could cover soft bodies. This highly customizable and flexible SPA-skin is ideal for providing proprioceptive sensing by covering pre-existing structures and robots bodies. Having few limitation of the surface quality, dynamics, or shape, these mechanical attributes allow potential applications in autonomous flexible braille, active surface pattern reconfiguration, distributed actuation and sensing for tactile interface improvements. In this paper, the authors present a proof-of-concept SPA-skin. The mechanical parameters, design criteria, sensor selection, and actuator construction process are illustrated. Two control schemes, actuation mode and force sensing mode, are also demonstrated with the latest prototype.

Motion planning for robots subject to holonomic constraints typically involves planning on constraint manifolds. In this paper we present the Tangent Space Rapidly Exploring Random Tree (TS-RRT) algorithm for planning on constraint manifolds. The key idea is to construct random trees not on the constraint manifold itself, but rather on tangent space approximations to the constraint manifold. Curvature-based methods are developed for constructing bounded tangent space approximations, as well as procedures for random node generation and bidirectional tree extension. Extensive numerical experiments suggest that the TS-RRT algorithm, despite its increased preprocessing and bookkeeping, outperforms existing constrained planning algorithms for a wide range of benchmark planning problems.