Configuration Estimation for Accurate Position Control of Large-Scale Soft Robots

There is a significant trend in robotics of exploring passively compliant and low inertia systems that can safely make contact with the environment. This paper defines many of the problems associated with developing effective control of soft, pneumatically actuated, inflatable robots, and proposes an approach to solving a subset of these problems. We show that we can obtain a global measurement of orientation for a given soft-robot link using two different types of sensors (not including motion capture). Given the orientation measurement, it is possible to estimate relative configurations of the soft actuators and joints. In order to validate the ability to control position and orientation at the end effector, we show a new method for calibrating the coordinate frames of two unrelated measurement systems. Then, using one of our configuration estimation methods, we demonstrate its viability by performing simple behaviors with a large-scale (approximately 1.5 m long) soft-robot platform attached to the K-Rex rover at NASA Ames in an outdoor environment. Our results also show the importance of soft-robot kinematic calibration and the sensitivity of a soft robot to simple perturbations in the structure like deflation and reinflation. Finally, we show that end effector error can be significantly reduced by doing a form of servoing. In summary, our approach and demonstrations show effective soft-robot configuration estimation and control for large-scale soft robots capable of performing manipulation tasks.