  Navigation and motion control of a robot to a destination are tasks that have
historically been performed with the assumption that contact with the
environment is harmful. This makes sense for rigid-bodied robots where obstacle
collisions are fundamentally dangerous. However, because many soft robots have
bodies that are low-inertia and compliant, obstacle contact is inherently safe.
As a result, constraining paths of the robot to not interact with the
environment is not necessary and may be limiting. In this paper, we
mathematically formalize interactions of a soft growing robot with a planar
environment in an empirical kinematic model. Using this interaction model, we
develop a method to plan paths for the robot to a destination. Rather than
avoiding contact with the environment, the planner exploits obstacle contact
when beneficial for navigation. We find that a planner that takes into account
and capitalizes on environmental contact produces paths that are more robust to
uncertainty than a planner that avoids all obstacle contact.
