3 citations · 6 across the 11 of their papers we have counts for
13 papers
InstanceBench: Diagnosing Referential Reasoning and Target Identity in Referring Expression Segmentation
Yuchen Li, Shaoyang Zhou, Yiran Wang +5
Referring Expression Segmentation (RES) links natural-language descriptions to pixel-level object masks. Yet standard evaluation provides limited insight into instance-level refere…
CoHuB: A Simulation Benchmark for Multi-Humanoid Collaboration
Hyunjin Park, Jebeom Chae, Minwoo Park +11
Many physical tasks in human environments require collaboration, from assisting a partner to jointly manipulating an object. Yet, existing humanoid benchmarks largely focus on sing…
Humanoid Safe Stop via Learned Stoppability Value
Junfeng Long, Pieter Abbeel, Koushil Sreenath +3
Humanoid robots responding to emergency stop commands typically execute a fixed maneuver, without reasoning about whether a safe stop is actually feasible from the current state. W…
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…
Symmetry-Aware Steering of Equivariant Diffusion Policies: Benefits and Limits
Minwoo Park, Junwoo Chang, Jongeun Choi +1
Equivariant diffusion policies (EDPs) combine the generative expressivity of diffusion models with the strong generalization and sample efficiency afforded by geometric symmetries.…
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…
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…
SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey
Joohwan Seo, Soochul Yoo, Junwoo Chang +6
Recent advances in deep learning and Transformers have driven major breakthroughs in robotics by employing techniques such as imitation learning, reinforcement learning, and LLM-ba…
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…
A Comparison Between Lie Group- and Lie Algebra- Based Potential Functions for Geometric Impedance Control
Joohwan Seo, Nikhil Potu Surya Prakash, Jongeun Choi +1
In this paper, a comparison analysis between geometric impedance controls (GICs) derived from two different potential functions on SE(3) for robotic manipulators is presented. The…
Clustering Techniques for Stable Linear Dynamical Systems with applications to Hard Disk Drives
Nikhil Potu Surya Prakash, Joohwan Seo, Jongeun Choi +1
In Robust Control and Data Driven Robust Control design methodologies, multiple plant transfer functions or a family of transfer functions are considered and a common controller is…
Denoising Heat-inspired Diffusion with Insulators for Collision Free Motion Planning
Junwoo Chang, Hyunwoo Ryu, Jiwoo Kim +5
Diffusion models have risen as a powerful tool in robotics due to their flexibility and multi-modality. While some of these methods effectively address complex problems, they often…
Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation
Hyunwoo Ryu, Jiwoo Kim, Hyunseok An +7
Diffusion generative modeling has become a promising approach for learning robotic manipulation tasks from stochastic human demonstrations. In this paper, we present Diffusion-EDFs…