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cs.RO2026
Multi-Robot Coordination for Planning under Context Uncertainty
Pulkit Rustagi, Kyle Hollins Wray, Sandhya Saisubramanian
Real-world robots often operate in settings where objective priorities depend on the underlying context of operation. When the underlying context is unknown apriori, multiple robot…
cs.RO2026
Adaptive Querying for Reward Learning from Human Feedback
Yashwanthi Anand, Nnamdi Nwagwu, Kevin Sabbe +2
Learning from human feedback is a popular approach to train robots to adapt to user preferences and improve safety. Existing approaches typically consider a single querying (intera…