4 papers
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…
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…
MEMOR-E: In-Context and Fine-Tuned LLM Personalization for Alzheimer's Assistive Robotics
Maissa Abir Smaili, Eren Sadikoglu, Ransalu Senanayake
Alzheimer's disease is a neurodegenerative disorder marked by progressive declines in memory and language that reduce independence in daily life, motivating socially assistive robo…
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…