Dynamic traversal of large gaps by insects and legged robots reveals a template (1911.02526v1)

Abstract: It is well known that animals can use neural and sensory feedback via vision, tactile sensing, and echolocation to negotiate obstacles. Similarly, most robots use deliberate or reactive planning to avoid obstacles, which relies on prior knowledge or high-fidelity sensing of the environment. However, during dynamic locomotion in complex, novel, 3-D terrains such as forest floor and building rubble, sensing and planning suffer bandwidth limitation and large noise and are sometimes even impossible. Here, we study rapid locomotion over a large gap, a simple, ubiquitous obstacle, to begin to discover general principles of dynamic traversal of large 3-D obstacles. We challenged the discoid cockroach and an open-loop six-legged robot to traverse a large gap of varying length. Both the animal and the robot could dynamically traverse a gap as large as 1 body length by bridging the gap with its head, but traversal probability decreased with gap length. Based on these observations, we developed a template that well captured body dynamics and quantitatively predicted traversal performance. Our template revealed that high approach speed, initial body pitch, and initial body pitch angular velocity facilitated dynamic traversal, and successfully predicted a new strategy of using body pitch control that increased the robot maximal traversal gap length by 50%. Our study established the first template of dynamic locomotion beyond planar surfaces and is an important step in expanding terradynamics into complex 3-D terrains.