1 citations · 1 across the 9 of their papers we have counts for
13 papers
OpenTac: An Open Ecosystem for Customizable, Scalable, and Transferable 3D Tactile Sensing
Ariel Slepyan, Geeta Chandra Raju Bethala, Jiafeng Gu +12
We present OpenTac, a novel sensor and a full-stack ecosystem for tactile skins that are highly customizable, scalable, and readily deployed in downstream robot control and learnin…
Continual Humanoid Motion Learning
Zhewen He, Hao Huang, Geeta Chandra Raju Bethala +4
Humanoid whole-body controllers can now track a diverse set of dynamic motions, but they are typically trained offline and then frozen, so teaching such a controller a new skill te…
Focus Where It Counts: A Salience-Driven Vision-Language Model for Low Vision Assistance
Jiazhao Liang, Hao Huang, Shuaihang Yuan +8
Vision-language models (VLMs) are rapidly progressing and offer promising capabilities for assistive technologies supporting persons with blindness or low vision. However, existing…
Learning Adaptive Safety Margins for Visual Navigation
Junyi Hu, Shuaihang Yuan, Geeta Chandra Raju Bethala +2
Robots in cluttered indoor spaces often fail not because they cannot generate collision-free paths, but because a fixed safety margin is mis-calibrated: conservative margins cause…
Immersive Social Interaction with VR and LLM-Assisted Humanoids
Niraj Pudasaini, Geeta Chandra Raju Bethala, Pranav Doma +2
Humanoid robots can extend human presence to remote, constrained, or hazardous environments, but existing teleoperation interfaces often require physically demanding motion trackin…
One-shot Adaptation of Humanoid Whole-body Motion with Walking Priors
Hao Huang, Geeta Chandra Raju Bethala, Shuaihang Yuan +4
Whole-body humanoid motion represents a fundamental challenge in robotics, requiring balance, coordination, and adaptability to enable human-like behaviors. However, existing metho…
Wavelet Policy: Lifting Scheme for Policy Learning in Long-Horizon Tasks
Hao Huang, Shuaihang Yuan, Geeta Chandra Raju Bethala +3
Policy learning focuses on devising strategies for agents in embodied artificial intelligence systems to perform optimal actions based on their perceived states. One of the key cha…
FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling
Yijie Deng, Shuaihang Yuan, Congcong Wen +4
Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot navigation. Existing approaches either…
Hierarchical Scoring with 3D Gaussian Splatting for Instance Image-Goal Navigation
Yijie Deng, Shuaihang Yuan, Geeta Chandra Raju Bethala +3
Instance Image-Goal Navigation (IIN) requires autonomous agents to identify and navigate to a target object or location depicted in a reference image captured from any viewpoint. W…
H2-COMPACT: Human-Humanoid Co-Manipulation via Adaptive Contact Trajectory Policies
Geeta Chandra Raju Bethala, Hao Huang, Niraj Pudasaini +5
We present a hierarchical policy-learning framework that enables a legged humanoid to cooperatively carry extended loads with a human partner using only haptic cues for intent infe…
Humanoid Agent via Embodied Chain-of-Action Reasoning with Multimodal Foundation Models for Zero-Shot Loco-Manipulation
Congcong Wen, Geeta Chandra Raju Bethala, Yu Hao +8
Humanoid loco-manipulation, which integrates whole-body locomotion with dexterous manipulation, remains a fundamental challenge in robotics. Beyond whole-body coordination and bala…
Integrating Retrospective Framework in Multi-Robot Collaboration
Jiazhao Liang, Hao Huang, Yu Hao +4
Recent advancements in Large Language Models (LLMs) have demonstrated substantial capabilities in enhancing communication and coordination in multi-robot systems. However, existing…
Socially-Aware Robot Navigation Enhanced by Bidirectional Natural Language Conversations Using Large Language Models
Congcong Wen, Yifan Liu, Geeta Chandra Raju Bethala +7
Robot navigation is crucial across various domains, yet traditional methods focus on efficiency and obstacle avoidance, often overlooking human behavior in shared spaces. With the…