3 accepted papers
Intelligent interaction with the real world requires robotic agents to jointly reason over high-level plans and low-level controls. This requirement is formalized in the task and motion planning (TAMP) problem, in which symbolic planning and continuous trajectory generation must be solved in a coord…
Efficient global optimization and sampling are fundamental challenges, particularly in fields such as robotics and reinforcement learning, where gradients may be unavailable or unreliable. In this context, jointly optimizing multiple solutions is a promising approach to avoid local optima. While Ste
Sequential decision-making and motion planning for robotic manipulation induce combinatorial complexity. For long-horizon tasks, especially when the environment comprises many objects that can be interacted with, planning efficiency becomes even more important. To plan such long-horizon tasks, we pr…