Quadruped robots have superior terrain adaptability and flexible movement capabilities than traditional robots. In this article, we innovatively apply it in person-following tasks, and propose an efficient motion planning scheme for quadruped robots to generate a flexible and effective trajectory in confined spaces. The method builds a real-time local costmap via onboard sensors, which involves both static and dynamic obstacles. And we exploit a simplified kinodynamic model and formulate the friction pyramids formed by ground reaction forces’ inequality constraints to ensure the executable of the optimized trajectory. In addition, we obtain the optimal following trajectory in the costmap completely based on the robot's rectangular footprint description, which ensures that it can walk through the narrow spaces avoiding collision. Finally, a receding horizon control strategy is employed to improve the robustness of motion in complex environments. The proposed motion planning framework is integrated on the quadruped robot JueYing and tested in simulation as well as real scenarios. It shows that the execution success rates in various scenes are all over 90%.

中文翻译：

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基于运动动力学模型的密闭空间四足机器人跟随人高效运动规划

四足机器人比传统机器人具有优越的地形适应能力和灵活的运动能力。在本文中，我们创新地将其应用于人员跟随任务，并提出了一种有效的四足机器人运动规划方案，以在有限空间内生成灵活有效的轨迹。该方法通过板载传感器构建实时本地成本图，其中包括静态和动态障碍物。并且我们利用简化的运动动力学模型并制定了由地面反作用力不等式约束形成的摩擦金字塔，以确保优化轨迹的可执行性。此外，我们完全根据机器人的矩形足迹描述在代价图中获得最佳跟随轨迹，确保它可以在狭窄的空间中行走，避免碰撞。最后，采用后退水平控制策略来提高复杂环境中运动的鲁棒性。所提出的运动规划框架集成在四足机器人 JueYing 上，并在模拟和真实场景中进行了测试。显示在各种场景下的执行成功率都在90%以上。