Abstract
Autonomous navigation methods can prevent robots becoming trapped between obstacles and ensure that they take the most efficient route. As mobile robots have a limited power supply, selecting the most efficient route is crucial. This letter presents a path-planning method for morphing soft robots in congested environments. The proposed method is suitable for all scales of robots and environments, from intra-organ biomedical navigation to search-and-rescue operations in cave networks. The method utilizes 3D Voronoi diagrams and Dijkstra's algorithm to calculate an optimal path that balances cost between the size and shape change of the robot and the length of the path. The Voronoi method is particularly suitable for circumferentially expanding robots because the waypoints generated lay where a device with a circular cross-section would naturally sit. The method is demonstrated by simulation in procedurally generated environments with either spherical or continuous obstacles to illustrate the effectiveness of the method for in-situ planning and as an aid to design. This letter provides a generic approach that has the potential to be easily adapted for many applications across healthcare, industry and space exploration.
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