  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.
