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20182026
most citedLearning from Suboptimal Demonstration via Self-Supervised Reward Regression

31 citations · 87 across the 20 of their papers we have counts for

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19 papers · 1 filter

cs.RO2026

Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video

Yunhai Han, Jianuo Qiu, Linhao Bai +14

Human manipulation videos are a convenient and intuitive source for robot learning. However, directly transferring human dexterity to robots remains challenging due to perception e…

cs.RO2025

Bi-Directional Mental Model Reconciliation for Human-Robot Interaction with Large Language Models

Nina Moorman, Michelle Zhao, Matthew B. Luebbers +5

In human-robot interactions, human and robot agents maintain internal mental models of their environment, their shared task, and each other. The accuracy of these representations d…

cs.RO2025

Towards Learning Scalable Agile Dynamic Motion Planning for Robosoccer Teams with Policy Optimization

Brandon Ho, Batuhan Altundas, Matthew Gombolay

In fast-paced, ever-changing environments, dynamic Motion Planning for Multi-Agent Systems in the presence of obstacles is a universal and unsolved problem. Be it from path plannin…

cs.RO2025

Use of Winsome Robots for Understanding Human Feedback (UWU)

Jessica Eggers, Angela Dai, Matthew C. Gombolay

As social robots become more common, many have adopted cute aesthetics aiming to enhance user comfort and acceptance. However, the effect of this aesthetic choice on human feedback…

cs.RO2024

ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics

Letian Chen, Nina Moorman, Matthew Gombolay

Reinforcement learning (RL) has demonstrated compelling performance in robotic tasks, but its success often hinges on the design of complex, ad hoc reward functions. Researchers ha…

cs.RO2024

Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems

Rohan Paleja, Michael Munje, Kimberlee Chang +2

Collaborative robots and machine learning-based virtual agents are increasingly entering the human workspace with the aim of increasing productivity and enhancing safety. Despite t…