CCDC Army Research Lab, Aberdeen Proving Ground, MD, United States of America.
Department of Mechanical Engineering, FAMU-FSU College of Engineering, Florida State University, Tallahassee, FL 32310, United States of America.
Bioinspir Biomim. 2021 Jan 25;16(2). doi: 10.1088/1748-3190/abd011.
The utility, efficiency, and reliability of legged robots has increased dramatically in recent years. Limbed robots are now capable of locomotion across a variety of terrains, however, achieving both rapid and efficient operation when ground conditions are complex or deformable is still challenging. Resistive terrains such as streams, snow, mud, littoral regions, and tall grass are an important class or set of complex and difficult terrain which are commonly found in the desired operating environments of legged robots. This work presents a reduced-order, dynamic model designed to capture the effect of these environments on the legs of a robot while running. This model, and an experimental platform, are used to evaluate the efficacy of a pair of strategies for adapting running to the inevitable slowing that occurs in resistive terrains. Simulation and experimental results show that intelligent retraction of the foot during flight has a more beneficial effect on the maximum achievable velocity and cost of transport of the runner than a 'punting gait' for a range of fluid depths. However, this performance gap became much smaller in deep fluids suggesting that fluid depth may drive transition from a foot retraction gait to a punting gait.
近年来，腿式机器人的实用性、效率和可靠性有了显著提高。现在，腿式机器人能够在各种地形上运动，但在地面条件复杂或可变形的情况下，实现快速高效的运行仍然具有挑战性。溪流、雪地、泥泞、滨海地区和高草丛等有阻力的地形是一类重要的复杂和困难地形，在腿式机器人期望的运行环境中经常会遇到这些地形。本工作提出了一个降阶动态模型，旨在捕捉这些环境对机器人腿部在跑动时的影响。该模型和一个实验平台用于评估两种策略的有效性，这两种策略用于适应在有阻力的地形中不可避免的减速。仿真和实验结果表明，在一系列流体深度下，与“踢腿步态”相比，脚部在飞行过程中的智能缩回对跑步者的最大可达速度和运输成本具有更有益的影响。然而，在深流体中，这种性能差距变得更小，这表明流体深度可能会促使从脚部缩回步态过渡到踢腿步态。
