Wheeled-legged robots are an attractive solution for versatile locomotion in challenging terrain. They combine the speed and efficiency of wheels with the ability of legs to traverse challenging terrain. In this letter, we present a trajectory optimization formulation for wheeled-legged robots that optimizes over the base and wheels’ positions and forces and takes into account the terrain information while computing the plans. This enables us to find optimal driving motions over challenging terrain. The robot is modeled as a single rigid-body, which allows us to plan complex motions and still keep a low computational complexity to solve the optimization quickly. The terrain map, together with the use of a stability constraint, allows the optimizer to generate feasible motions that cannot be discovered without taking the terrain information into account. The optimization is formulated as a Nonlinear Programming (NLP) problem and the reference motions are tracked by a hierarchical whole-body controller that computes the torque actuation commands for the robot. The trajectories have been experimentally verified on quadrupedal robot ANYmal equipped with non-steerable torque-controlled wheels. Our trajectory optimization framework enables wheeled quadrupedal robots to drive over challenging terrain, e.g., steps, slopes, stairs, while negotiating these obstacles with dynamic motions.

中文翻译：

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轮足四足机器人在挑战性地形中行驶的轨迹优化


轮腿机器人是在具有挑战性的地形中进行多功能移动的有吸引力的解决方案。它们将车轮的速度和效率与腿部穿越具有挑战性的地形的能力结合起来。在这封信中，我们提出了轮腿机器人的轨迹优化公式，该公式优化了底座和轮子的位置和力，并在计算计划时考虑了地形信息。这使我们能够在具有挑战性的地形上找到最佳的驾驶动作。机器人被建模为单个刚体，这使我们能够规划复杂的运动，并仍然保持较低的计算复杂度来快速解决优化问题。地形图与稳定性约束一起使用，允许优化器生成在不考虑地形信息的情况下无法发现的可行运动。优化被表述为非线性编程（NLP）问题，参考运动由分层全身控制器跟踪，该控制器计算机器人的扭矩驱动命令。这些轨迹已在配备不可转向扭矩控制轮的四足机器人 ANYmal 上进行了实验验证。我们的轨迹优化框架使轮式四足机器人能够在具有挑战性的地形上行驶，例如台阶、斜坡、楼梯，同时通过动态运动越过这些障碍物。