Visual sensing of environmental geometry allows robots to use artificial potential fields to avoid sparse obstacles. Yet robots must further traverse cluttered large obstacles for applications like search and rescue through rubble and planetary exploration across Martain rocks. Recent studies discovered that to traverse cluttered large obstacles, multi-legged insects and insect-inspired robots make strenuous transitions across locomotor modes with major changes in body orientation. When viewed on a potential energy landscape resulting from locomotor-obstacle physical interaction, these are barrier-crossing transitions across landscape basins. This potential energy landscape approach may provide a modeling framework for cluttered large obstacle traversal. Here, we take the next step toward this vision by testing whether force sensing allows the reconstruction of the potential energy landscape. We developed a cockroach-inspired, minimalistic robot capable of sensing obstacle contact forces and torques around its body as it propelled forward against a pair of cluttered grass-like beam obstacles. We performed measurements over many traverses with systematically varied body orientations. Despite the forces and torques not being fully conservative, they well-matched the potential energy landscape gradients and the landscape reconstructed from them well-matched ground truth. In addition, inspired by cockroach observations, we found that robot head oscillation during traversal further improved the accuracies of force sensing and landscape reconstruction. We still need to study how to reconstruct landscape during a single traverse, as in applications, robots have little chance to use multiple traverses to sample the environment systematically and how to find landscape saddles for least-effort transitions to traverse.

翻译：视觉感知环境几何结构使机器人能够利用人工势场避开稀疏障碍物。然而，在诸如废墟搜救和火星岩石间行星探测等应用中，机器人仍需穿越杂乱的大障碍物。近年研究发现，为穿越杂乱大障碍物，多足昆虫与仿昆虫机器人需在身体姿态发生显著变化的情况下，进行跨运动模式的费力切换。从运动体-障碍物物理交互产生的势能景观视角观察，这些切换对应着势能盆地间的跨势垒跃迁。这种势能景观方法或可为杂乱大障碍物穿越提供建模框架。本文向这一目标迈出关键一步，通过实验验证触力传感能否实现势能景观的重构。我们研制了一种蟑螂启发的最小化机器人，能在推动自身穿越一对杂乱草状梁式障碍物时，感知身体周围的障碍物接触力与力矩。通过系统变化身体姿态进行多次穿越测量。尽管力与力矩并非完全保守，它们与势能景观梯度高度吻合，据此重构的景观与真实值匹配良好。此外，受蟑螂观测启发，发现机器人在穿越过程中的头部摆动可进一步提升触力传感与景观重构的精度。未来仍需研究如何实现单次穿越过程中的景观重构——因实际应用中机器人难以通过多次穿越系统采样环境——以及如何识别景观鞍点以实现最小能耗的穿越过渡。