This study proposes an integrated task and motion planning method for dynamic locomotion in partially observable environments with multi-level safety guarantees. This layered planning framework is composed of a high-level symbolic task planner and a low-level phase-space motion planner. A belief abstraction at the task planning level enables belief estimation of dynamic obstacle locations and guarantees navigation safety with collision avoidance. The high-level task planner, i.e., a two-level navigation planner, employs linear temporal logic for a reactive game synthesis between the robot and its environment while incorporating low-level safe keyframe policies into formal task specification design. The synthesized task planner commands a series of locomotion actions including walking step length, step height, and heading angle changes, to the underlying keyframe decision-maker, which further determines the robot center-of-mass apex velocity keyframe. The low-level phase-space planner uses a reduced-order locomotion model to generate non-periodic trajectories meeting balancing safety criteria for straight and steering walking. These criteria are characterized by constraints on locomotion keyframe states, and are used to define keyframe transition policies via viability kernels. Simulation results of a Cassie bipedal robot designed by Agility Robotics demonstrate locomotion maneuvering in a three-dimensional, partially observable environment consisting of dynamic obstacles and uneven terrain.

中文翻译：

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在具有不平坦地形的部分可观察环境中实现安全移动导航

本研究提出了一种在具有多级安全保证的部分可观察环境中进行动态运动的集成任务和运动规划方法。该分层规划框架由高级符号任务规划器和低级相空间运动规划器组成。任务规划级别的置信抽象可以实现动态障碍物位置的置信估计，并通过避免碰撞来保证导航安全。高级任务规划器，即两级导航规划器，采用线性时间逻辑进行机器人与其环境之间的反应性博弈综合，同时将低级安全关键帧策略纳入正式的任务规范设计。合成任务规划器命令一系列运动动作，包括步行步长、步高和航向角变化，到基础关键帧决策者，它进一步确定机器人质心顶点速度关键帧。低级相空间规划器使用降阶运动模型来生成满足直线和转向行走平衡安全标准的非周期性轨迹。这些标准的特点是对运动关键帧状态的约束，并用于通过可行性内核定义关键帧转换策略。Agility Robotics 设计的 Cassie 双足机器人的仿真结果展示了在由动态障碍物和不平坦地形组成的三维、部分可观察环境中的运动机动。低级相空间规划器使用降阶运动模型来生成满足直线和转向行走平衡安全标准的非周期性轨迹。这些标准的特点是对运动关键帧状态的约束，并用于通过可行性内核定义关键帧转换策略。Agility Robotics 设计的 Cassie 双足机器人的仿真结果展示了在由动态障碍物和不平坦地形组成的三维、部分可观察环境中的运动机动。低级相空间规划器使用降阶运动模型来生成满足直线和转向行走平衡安全标准的非周期性轨迹。这些标准的特点是对运动关键帧状态的约束，并用于通过可行性内核定义关键帧转换策略。Agility Robotics 设计的 Cassie 双足机器人的仿真结果展示了在由动态障碍物和不平坦地形组成的三维、部分可观察环境中的运动机动。