4 citations · 10 across the 12 of their papers we have counts for
12 papers
Embodied Human-Robot Interaction via Acoustics: A MARL Approach with AcoustoBots for Spatial Data Physicalization
Shiqi Liu, Narsimlu Kemsaram, Prateek Mittal +2
Traditional data physicalization is often static and disconnected from real environments, limiting its ability to convey embodied spatial dynamics and engage users. To address this…
Pushing Forward Pareto Frontiers of Proactive Agents with Behavioral Agentic Optimization
Yihang Yao, Zhepeng Cen, Haohong Lin +6
Proactive large language model (LLM) agents aim to actively plan, query, and interact over multiple turns, enabling efficient task completion beyond passive instruction following a…
APEX: Learning Adaptive High-Platform Traversal for Humanoid Robots
Yikai Wang, Tingxuan Leng, Changyi Lin +5
Humanoid locomotion has advanced rapidly with deep reinforcement learning (DRL), enabling robust feet-based traversal over uneven terrain. Yet platforms beyond leg length remain la…
Query-Centric Diffusion Policy for Generalizable Robotic Assembly
Ziyi Xu, Haohong Lin, Shiqi Liu +1
The robotic assembly task poses a key challenge in building generalist robots due to the intrinsic complexity of part interactions and the sensitivity to noise perturbations in con…
LocoTouch: Learning Dynamic Quadrupedal Transport with Tactile Sensing
Changyi Lin, Yuxin Ray Song, Boda Huo +9
Quadrupedal robots have demonstrated remarkable agility and robustness in traversing complex terrains. However, they struggle with dynamic object interactions, where contact must b…
QuietPaw: Learning Quadrupedal Locomotion with Versatile Noise Preference Alignment
Yuyou Zhang, Yihang Yao, Shiqi Liu +7
When operating at their full capacity, quadrupedal robots can produce loud footstep noise, which can be disruptive in human-centered environments like homes, offices, and hospitals…
Learning Multi-Agent Loco-Manipulation for Long-Horizon Quadrupedal Pushing
Yuming Feng, Chuye Hong, Yaru Niu +6
Recently, quadrupedal locomotion has achieved significant success, but their manipulation capabilities, particularly in handling large objects, remain limited, restricting their us…
Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications
Xilun Zhang, Shiqi Liu, Peide Huang +4
Sim-to-real transfer remains a significant challenge in robotics due to the discrepancies between simulated and real-world dynamics. Traditional methods like Domain Randomization o…
OASIS: Conditional Distribution Shaping for Offline Safe Reinforcement Learning
Yihang Yao, Zhepeng Cen, Wenhao Ding +5
Offline safe reinforcement learning (RL) aims to train a policy that satisfies constraints using a pre-collected dataset. Most current methods struggle with the mismatch between im…
Creative Robot Tool Use with Large Language Models
Mengdi Xu, Peide Huang, Wenhao Yu +7
Tool use is a hallmark of advanced intelligence, exemplified in both animal behavior and robotic capabilities. This paper investigates the feasibility of imbuing robots with the ab…
Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report
Jielin Qiu, Jiacheng Zhu, Shiqi Liu +7
Automated interpretation of electrocardiograms (ECG) has garnered significant attention with the advancements in machine learning methodologies. Despite the growing interest, most…
SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark under Multiple Environments
Hanjiang Hu, Baoquan Yang, Zhijian Qiao +6
Different environments pose a great challenge to the outdoor robust visual perception for long-term autonomous driving, and the generalization of learning-based algorithms on diffe…