Dynamic traversal of large gaps by insects and legged robots reveals a template

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, 3D terrains, such as a 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 the general principles of the dynamic traversal of large 3D 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 one 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 accurately captured body dynamics and quantitatively predicted traversal performance. Our template revealed that a high approach speed, initial body pitch, and initial body pitch angular velocity facilitated dynamic traversal, and successfully predicted a new strategy for using body pitch control that increased the robot's 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 3D terrains.

An obstacle disturbance selection framework: emergent robot steady states under repeated collisions

“…We hypothesize that the disturbances from obstacles can be regarded as opportunities to enhance mobility in complex environments (Figure 1). Biological studies have demonstrated that animals (Kinsey and McBrayer, 2018; Kohlsdorf and Biewener, 2006; McInroe et al, 2016; Wilshin et al, 2017) can coordinate their appendages or body segments (Schiebel et al, 2019; Zhong et al, 2018) to adjust the timing and positions of environment engagement (Gart and Li, 2018; Gart et al, 2018; Li et al, 2015) to achieve effective locomotion. In analogy to the selected leg sequence timing in biological locomotors, Johnson and Koditschek (2013) demonstrated that with a human-programmed leg activation sequence, a hexapedal robot can jump up a vertical cliff by using its front legs to hook on the cliff edge while pushing its rear legs against the vertical surface.…”

Going the distance: The biomechanics of gap‐crossing behaviors

“…When more than 50% of the animal's body mass is extended over the gap, passive counterbalancing without grip is not physically possible. Evidence of the influence of pitching on gap‐crossing performance can be found in snakes (Jayne & Riley, ) and cockroaches (Gart et al, ). The brown tree snake uses more tail wrapping during lunging than during cantilever bridges, where typically the weight of the animal on the origin support provides a passive counterweight against pitching (Jayne & Riley, ).…”

Modulation of Robot Orientation Via Leg-Obstacle Contact Positions

“…In contrast, robots typically avoid most collisions and contacts with their physical environments and treat large disturbances as "obstacles" because our limited understanding of contact reaction forces precludes their effective use. Without a better understanding of the dynamics of repeated locomotorobstacle interactions [3], [5], [6] obtaining such understanding from systematic experiments in simplified settings [7], [8], [9], [10], [11], [12], [5], [13]. While the vast parameter space presented by any natural environment presents daunting challenges to analysis, this paper seeks to build on recent progress in extracting a highly abstracted but physically revealing model of periodic legged gaits interacting with periodically structured obstacle fields [13].…”