This study introduces the Hybrid Sequential Manipulation Planner (H-MaP), a novel approach that iteratively does motion planning using contact points and waypoints for complex sequential manipulation tasks in robotics. Combining optimization-based methods for generalizability and sampling-based methods for robustness, H-MaP enhances manipulation planning through active contact mode switches and enables interactions with auxiliary objects and tools. This framework, validated by a series of diverse physical manipulation tasks and real-robot experiments, offers a scalable and adaptable solution for complex real-world applications in robotic manipulation.

翻译：摘要：本研究提出了混合顺序操作规划器（H-MaP），这是一种新颖的方法，通过接触点和路径点迭代地进行运动规划，以应对机器人中复杂的顺序操作任务。H-MaP结合了基于优化的方法以实现通用性，以及基于采样的方法以增强鲁棒性，通过主动接触模式切换提升了操作规划能力，并支持与辅助物体和工具的交互。该框架通过一系列多样化的物理操作任务和真实机器人实验进行了验证，为机器人操作领域的复杂现实应用提供了一种可扩展且自适应的解决方案。