New TASP approach integrates diverse robot skills for complex tasks

Researchers have developed a new hierarchical planning approach called Task and Skill Planning (TASP) for robots. This method integrates diverse, pre-existing skills, including learned, force-controlled, and black-box policies, into a single planning framework. The approach uses Composable Interaction Primitives (CIPs) to connect these skills, allowing for both planning-time refinement and execution-time adjustments. TASP has been successfully demonstrated on real-world bimanual and mobile manipulators, enabling them to solve complex, long-horizon tasks. AI

IMPACT Enables robots to combine diverse skills for more complex and long-horizon tasks.

RANK_REASON The cluster contains a research paper detailing a new method for robot planning. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• Benned Hedegaard
• bimanual manipulator
• Composable Interaction Primitives
• mobile manipulator
• Task and Skill Planning

• paper
• other

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