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 article, 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.

中文翻译：

---

通过利用与环境的接触对软生长机器人进行鲁棒导航

机器人到目的地的导航和运动控制是历史上执行的任务，假设与环境接触是有害的。这对于刚体机器人来说是有意义的，因为障碍物碰撞从根本上来说是危险的。然而，由于许多软机器人具有低惯性且柔顺的身体，因此接触障碍物本质上是安全的。因此，将机器人的路径限制为不与环境交互是不必要的，并且可能是限制性的。在本文中，我们在一个经验运动学模型中数学形式化了软生长机器人与平面环境的相互作用。使用这个交互模型，我们开发了一种方法来规划机器人到目的地的路径。与其避免与环境接触，规划器在有利于导航时利用障碍物接触。我们发现，与避免所有障碍物接触的规划者相比，考虑并利用环境接触的规划者产生的路径对不确定性更稳健。