An obstacle-interaction planning method for navigation of actuated vine robots
Mario Selvaggio, Lynher Ramirez, Nicholas D. Naclerio, Bruno Siciliano, Elliot W. Hawkes
Abstract
The field of soft robotics is grounded on the idea that, due to their inherent compliance, soft robots can safely interact with the environment. Thus, the development of effective planning and control pipelines for soft robots should incorporate reliable robot-environment interaction models. This strategy enables soft robots to effectively exploit contacts to autonomously navigate and accomplish tasks in the environment. However, for a class of soft robots, namely vine-inspired, tip-extending or "vine" robots, such interaction models and the resulting planning and control strategies do not exist. In this paper, we analyze the behavior of vine robots interacting with their environment and propose an obstacle-interaction model that characterizes the bending and wrinkling deformation induced by the environment. Starting from this, we devise a novel obstacle-interaction planning method for these robots. We show how obstacle interactions can be effectively leveraged to enlarge the set of reachable workspace for the robot tip, and verify our findings with both simulated and real experiments. Our work improves the capabilities of this new class of soft robot, helping to advance the field of soft robotics.