In this paper, we propose a novel approach on controlling wheel-legged quadrupedal robots using pose optimization and force control via quadratic programming (QP). Our method allows the robot to leverage wheel torques to navigate the terrain while keeping the wheel traction and balancing the robot body. In detail, we present a rigid body dynamics with wheels that can be used for real-time balancing control of wheel-legged robots. In addition, we introduce an effective pose optimization method for wheel-legged robot's locomotion over uneven terrains with ramps and stairs. The pose optimization utilized a nonlinear programming (NLP) solver to solve for the optimal poses in terms of joint positions based on kinematic and contact constraints during a stair-climbing task with rolling wheels. In simulation, our approach has successfully validated for the problem of a wheel-legged robot climbing up a 0.34m stair with a slope angle of 80 degrees and shown its versatility in multiple-stair climbing with varied stair runs and rises with wheel traction. Experimental validation on the real robot demonstrated the capability of climbing up on a 0.25m stair with a slope angle of 30 degrees.

中文翻译：

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不平坦地形导航的轮腿机器人平衡控制与姿态优化

在本文中，我们提出了一种通过二次规划 (QP) 使用姿势优化和力控制来控制轮腿四足机器人的新方法。我们的方法允许机器人利用车轮扭矩来导航地形，同时保持车轮牵引力和平衡机器人身体。详细地，我们提出了一种带轮子的刚体动力学，可用于轮腿机器人的实时平衡控制。此外，我们介绍了一种有效的姿势优化方法，用于轮腿机器人在具有坡道和楼梯的不平坦地形上的运动。姿势优化利用非线性规划 (NLP) 求解器，在滚轮爬楼梯任务期间，基于运动学和接触约束，根据关节位置求解最佳姿势。在模拟中，我们的方法已经成功地验证了轮腿机器人爬上 0.34m 坡度为 80 度的楼梯的问题，并展示了它在多楼梯爬坡中的多功能性，不同的楼梯运行和通过车轮牵引上升。在真实机器人上的实验验证证明了爬上 0.25m 坡度为 30 度的楼梯的能力。