Long-term non-prehensile planar manipulation is a challenging task for robot planning and feedback control. It is characterized by underactuation, hybrid control, and contact uncertainty. One main difficulty is to determine both the continuous and discrete contact configurations, e.g., contact points and modes, which requires joint logical and geometrical reasoning. To tackle this issue, we propose a demonstration-guided hierarchical optimization framework to achieve offline task and motion planning (TAMP). Our work extends the formulation of the dynamics model of the pusher-slider system to include separation mode with face switching mechanism, and solves a warm-started TAMP problem by exploiting human demonstrations. We show that our approach can cope well with the local minima problems currently present in the state-of-the-art solvers and determine a valid solution to the task. We validate our results in simulation and demonstrate its applicability on a pusher-slider system with a real Franka Emika robot in the presence of external disturbances.

翻译：长期的、非痛苦的平板操作是机器人规划和反馈控制的一项艰巨任务,其特点是动作不足、混合控制和接触不确定,主要困难之一是确定连续和离散的接触配置,例如联络点和模式,这需要共同的逻辑和几何推理。为了解决这一问题,我们提议了一个示范性指导的等级优化框架,以实现脱机任务和运动规划(TAMP)。我们的工作将推推机滑板系统的动态模型的形成扩大到包括面部切换机制的分离模式,并通过利用人类演示解决一个热点启动的TAMP问题。我们表明,我们的方法能够很好地应对目前处于最先进的解决方案中的当地微型问题,并确定任务的有效解决方案。我们在模拟中验证了我们的结果,并证明它适用于推推机滑板系统,在出现外部动乱时使用真正的Franka Emika机器人。</s>