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We present a pneumatic actuator capable of changing length by 1000%, applying both pushing and pulling forces, and independently modulating its length and stiffness. These characteristics are enabled by individually addressable internal and external chambers that work antagonistically against one another. The high deformation with low hysteresis is achieved by wrinkling of thin materials that are assumed to be inextensible but flexible, as opposed to stretchable. A model for the actuator is presented and validated with experimental results, showing capabilities of high strain, pushing and pulling, and independent control of length and stiffness. These charac- teristics are motivated by the application of a compliant truss robot. Accordingly, we show a simple grounded tetrahedron with three actuator elements and three static elements. We demonstrate motion of the tetrahedron apex against external loads and the ability of the structure to vary its stiffness. The actuator offers a unique set of characteristics that could increase the capabilities of soft robotic devices. 

For many types of robots, avoiding obstacles is necessary to prevent damage to the robot and environment. As a result, obstacle avoidance has historically been an im- portant problem in robot path planning and control. Soft robots represent a paradigm shift with respect to obstacle avoidance because their low mass and compliant bodies can make collisions with obstacles inherently safe. Here we consider the benefits of intentional obstacle collisions for soft robot navigation. We develop and experimentally verify a model of robot-obstacle interaction for a tip-extending soft robot. Building on the obstacle interaction model, we develop an algorithm to determine the path of a growing robot that takes into account obstacle collisions. We find that obstacle collisions can be beneficial for open-loop navigation of growing robots because the obstacles passively steer the robot, both reducing the uncertainty of the location of the robot and directing the robot to targets that do not lie on a straight path from the starting point. Our work shows that for a robot with predictable and safe interactions with obstacles, target locations in a cluttered, mapped environment can be reached reliably by simply setting the initial trajectory. This has implications for the control and design of robots with minimal active steering.