4 citations · 9 across the 21 of their papers we have counts for
8 papers · 1 filter
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…
A Chain-of-Thought Subspace Meta-Learning for Few-shot Image Captioning with Large Vision and Language Models
Hao Huang, Shuaihang Yuan, Yu Hao +2
A large-scale vision and language model that has been pretrained on massive data encodes visual and linguistic prior, which makes it easier to generate images and language that are…
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…