The heavy-load legged robot has strong load carrying capacity and can adapt to various unstructured terrains. But the large weight results in higher requirements for motion stability and environmental perception ability. In order to utilize force sensing information to improve its motion performance, in this paper, we propose a finite state machine model for the swing leg in the static gait by imitating the movement of the elephant. Based on the presence or absence of additional terrain information, different trajectory planning strategies are provided for the swing leg to enhance the success rate of stepping and save energy. The experimental results on a novel quadruped robot show that our method has strong robustness and can enable heavy-load legged robots to pass through various complex terrains autonomously and smoothly.

翻译：重载腿足机器人具有强大的负载能力，并能适应各种非结构化地形。但其大重量特征对运动稳定性和环境感知能力提出了更高要求。为利用力传感信息提升运动性能，本文通过模仿大象的运动方式，提出了静态步态下的摆腿有限状态机模型。根据是否存在额外地形信息，为摆腿设计了不同的轨迹规划策略，以增强落脚成功率并节省能量。在一台新型四足机器人上的实验结果表明，该方法具有强鲁棒性，能使重载腿足机器人自主、平稳地通过各类复杂地形。