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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.RO2026

Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences

Taehyung Kim, Gwangmo Lee, Minjun Chang +2

The paper proposes Preference-based REward Clustering (PREC), a method that groups users with similar preferences and learns a compact set of reward models from binary feedback to…

cs.RO2026

Multi-Robot Motion Planning from Vision and Language using Heat-Inspired Diffusion

Jebeom Chae, Junwoo Chang, Seungho Yeom +2

Diffusion models have recently emerged as powerful tools for robot motion planning by capturing the multi-modal distribution of feasible trajectories. However, their extension to m…

cs.RO2026

Geometric Formulation of Unified Force-Impedance Control on SE(3) for Robotic Manipulators

Joohwan Seo, Nikhil Potu Surya Prakash, Soomi Lee +4

In this paper, we present an impedance control framework on the SE(3) manifold, which enables force tracking while guaranteeing passivity. Building upon the unified force-impedance…

cs.LG2026

Partially Equivariant Reinforcement Learning in Symmetry-Breaking Environments

Junwoo Chang, Minwoo Park, Joohwan Seo +3

Group symmetries provide a powerful inductive bias for reinforcement learning (RL), enabling efficient generalization across symmetric states and actions via group-invariant Markov…

cs.RO2026

EquiContact: A Hierarchical SE(3) Vision-to-Force Equivariant Policy for Spatially Generalizable Contact-rich Tasks

Joohwan Seo, Arvind Kruthiventy, Soomi Lee +5

This paper presents a framework for learning vision-based robotic policies for contact-rich manipulation tasks that generalize spatially across task configurations. We focus on ach…

cs.RO2026

Group-Invariant Unsupervised Skill Discovery: Symmetry-aware Skill Representations for Generalizable Behavior

Junwoo Chang, Joseph Park, Roberto Horowitz +2

Unsupervised skill discovery aims to acquire behavior primitives that improve exploration and accelerate downstream task learning. However, existing approaches often ignore the geo…