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cs.RO2026
ROOT: Discovering Rewards for User-Specified Embodied Behaviors
Eren Sadikoglu, Aditya Taparia, Xinyuan Liu +1
Reinforcement learning for embodied control remains constrained by the difficulty of reward specification. Although recent large language model (LLM)-based methods can synthesize r…
cs.RO2026
Physical Agentic AI: An Architecture for Orchestrating a Robot Crew with LLMs
Xinyuan Liu, Eren Sadikoglu, Riana Chatterjee +1
Agentic AI frameworks interpret open-ended task goals and decompose them into multi-step plans. Richer information about embodiment-specific capabilities, physical preconditions, a…
cs.RO2026
Humanoid Factors: Design Principles for AI Humanoids in Human Worlds
Xinyuan Liu, Eren Sadikoglu, Ransalu Senanayake +1
Human factors research has long focused on optimizing environments, tools, and systems to account for human performance. Yet, as humanoid robots begin to share our workplaces, home…