Supplementary video for paper 22-TIE-4910 submitted to IEEE Transactions on Industrial Electronics

Legged robots have demonstrated high potential when dealing with rough terrain, for which an efficient motion planner becomes crucial. This paper presents a novel approach for quadrupedal robot motion planning on rough terrain, which is both conceptually straightforward and computationally efficient. Implementing the concept of workspace constitutes the cornerstone of this method: both body poses and swing-leg footholds are chosen within their corresponding workspace. A novel approach called "cross-diagonal method'' is developed to facilitate the search for new body poses. Based on the obtained body pose, the foothold for a swing leg selected within its foot workspace satisfies the reachability constraint automatically. The proposed motion planning scheme is integrated with an elevation mapping module and a state estimation module, enabling quadrupedal robots to travel through uneven terrains with high efficiency. The significance of this work is validated through simulation and physical experiments with a quadrupedal robot, which achieves high success rates in overcoming difficult terrains without prior knowledge of the environment. This approach offers advantages of high computational efficiency, simplicity, and adaptability to different types of terrains, making it a promising solution for real-world applications.

在崎岖地形处理方面，四足机器人展现出巨大的潜力，因此，一个高效的运动规划器变得至关重要。本文提出了一种新颖的四足机器人在崎岖地形上的运动规划方法，该方法在概念上简洁明了，在计算上高效可行。构建工作空间的概念构成了该方法的基石：既包括身体姿态，也包括摆动腿的踏点，均在对应的工作空间内进行选择。为促进新身体姿态的搜索，开发了一种名为“交叉对角线法”的新方法。基于获得的身体姿态，摆动腿在足部工作空间内选择的踏点能够自动满足可达性约束。所提出的运动规划方案与高度映射模块和状态估计模块相结合，使得四足机器人能够以高效率穿越不均匀地形。通过四足机器人的仿真和物理实验验证了该工作的意义，该机器人能够在无需了解环境的情况下，以高成功率克服复杂地形。该方法在计算效率、简洁性和对不同类型地形的适应性方面具有优势，因此，它对于现实世界的应用具有广阔的前景。