collaborators

11 papers

cs.RO2026

Flow Matching for Robot Foundation Models

Kuangji Zuo, Tuo An, Xinying Guo +9

Flow matching is a common generative recipe for robot foundation models. Vision-language-action models (VLAs) generate action chunks, while world-action models (WAMs) additionally…

cs.RO2026

mmHRI: Towards Privacy-Preserving Human-Robot Interaction with Millimeter-Wave Radar

Junqiao Fan, Yuxuan Hu, Bofan Lyu +7

Assistive robots increasingly operate in many human-centered environments and perform various human-robot interaction (HRI) tasks, such as object delivery. However, most existing H…

cs.RO2026

ADAPT: Analytical Disturbance-Aware Policy Training for Humanoid Locomotion

Bofan Lyu, Jindou Jia, Kuangji Zuo +7

Humanoids deployed in human-centered environments must handle force-interactive tasks, where external contacts introduce unexpected disturbances that disrupt locomotion accuracy an…

cs.RO2026

EM-Fall: Embodied mmWave Sensing for Day-and-Night Fall Detection on Humanoid Robots

Yanshuo Lu, Yuxuan Hu, Shenghai Yuan +5

Falls are one of the leading causes of injury and hospitalization among elderly individuals, making reliable fall awareness an essential capability for safety monitoring in residen…

cs.RO2026

Gaze2Act: Gaze-Conditioned Vision-Language-Action Policies for Interactive Robot Manipulation

Kuangji Zuo, Gen Li, Bofan Lyu +9

Vision-Language-Action (VLA) models have recently shown strong potential for robot learning by following language instructions. However, in practice, language alone is often insuff…

cs.RO2026

MARS Policy: Multimodality Only When It Matters

Jindou Jia, Tuo An, Yuxuan Hu +7

Imitation learning has become a cornerstone for solving complex robotic manipulation tasks. In particular, multimodality, which enables robots to capture diverse yet valid behavior…

cs.CV2026

OccamToken: Efficient VLM Inference with Training-Free and Budget-Adaptive Token Pruning

Geng Li, Guohao Chen, Ting Chen +6

Vision-language models (VLMs) rely on long visual token sequences for visual understanding, making the prefill stage expensive in both computation and memory. Most existing pruning…

cs.CV2026

CompassAD: Intent-Driven 3D Affordance Grounding in Functionally Competing Objects

Jingliang Li, Jindou Jia, Tuo An +7

When told to "cut the cake," a robot must choose the knife over nearby scissors, despite both objects affording the same cutting function. In real-world scenes, multiple objects ma…

cs.RO2026

Feedback World Model Enables Precise Guidance of Diffusion Policy

Tuo An, Jindou Jia, Gen Li +8

World models aim to improve robotic decision making by predicting the consequences of actions. However, in practice, their predictions often become unreliable once the robot encoun…

cs.RO2026

RoboForge: Physically Optimized Text-guided Whole-Body Locomotion for Humanoids

Xichen Yuan, Zhe Li, Bofan Lyu +4

While generative models have become effective at producing human-like motions from text, transferring these motions to humanoid robots for physical execution remains challenging. E…

cs.CV2024

3D Kinematics Estimation from Video with a Biomechanical Model and Synthetic Training Data

Zhi-Yi Lin, Bofan Lyu, Judith Cueto Fernandez +3

Accurate 3D kinematics estimation of human body is crucial in various applications for human health and mobility, such as rehabilitation, injury prevention, and diagnosis, as it he…