Task Frame

Task frame research focuses on optimally defining the coordinate systems and representations used to plan and execute robotic tasks, aiming to improve efficiency and robustness in complex scenarios. Current efforts involve developing automated methods for task frame selection, integrating task and motion planning algorithms (e.g., using logic-geometric programming or SMT solvers), and optimizing data organization for multi-task learning. These advancements are crucial for enabling robots to perform contact-rich manipulations, multi-robot coordination, and human-robot collaboration in dynamic environments, ultimately leading to more adaptable and efficient robotic systems.