One of the fundamental fields of research is motion planning. Mobile manipulators present a
unique set of challenges for the planning algorithms, as they are usually kinematically …

Autonomous robots are increasingly served in real-world unstructured human environments
with complex long-horizon tasks, such as restaurant serving and office delivery. Task and …

Task and motion planning (TAMP) integrates high-level task planning and low-level motion
planning to equip robots with the autonomy to effectively reason over long-horizon, dynamic …

Task and Motion Planning has made great progress in solving hard sequential manipulation
problems. However, a gap between such planning formulations and control methods for …

The booming of electric vehicles demands efficient battery disassembly for recycling to be
environment-friendly. Due to the unstructured environment and high uncertainties, battery …

This paper focuses on motion planning for mobile manipulators, which includes planning for
both the mobile base and the manipulator. A hierarchical motion planner is proposed that …

Sequential decision-making and motion planning for robotic manipulation induce
combinatorial complexity. For long-horizon tasks, especially when the environment …

Learning from Demonstration (LfD) stands as an efficient framework for imparting human-
like skills to robots. Nevertheless, designing an LfD framework capable of seamlessly …

Task and Motion Planning (TAMP) has made strides in complex manipulation tasks, yet the
execution robustness of the planned solutions remains overlooked. In this work, we propose …

Robot motion planning has made vast advances over the past decades, but the challenge
remains: robot mobile manipulators struggle to plan long-range whole-body motion in …