15 citations · 29 across the 14 of their papers we have counts for
19 papers
Proprioceptive Sketches as Long-Horizon Intent for Generative Action Policies
Fangyuan Wang, Songhao Huang, Haoxiang Sun +5
Generative robot policies predict short action chunks but lack explicit long-horizon intent. Recent methods expose longer-horizon structure through language plans, subgoal images,…
Robot-GST: geometry-aware spatial-temporal robot policy representation and evaluation
Sichao Liu, Zekun Wang, Lixuan Tang +6
Robotic manipulation policies are advancing rapidly with increasing reliance on vision-language models for end-to-end decision making. However, reliable deployment remains challeng…
Achieve What You Imagined: Learning to Align Actions with Visual Plans
Yuheng Qiao, Ziran Wei, Xiaohan Wang +5
World-action models can jointly predict future visual observations and robot actions. However, discrepancies may exist between their visual predictions and the consequences implied…
CAMP: Cooperative Arm-Hand Motion Planning in Constrained Spaces
Ziyuan Wang, Yunlong Shan, Fei Mo +6
Coordinated arm-hand motion planning is fundamental to dexterous robotic manipulation in complex and constrained environments. A straightforward solution is to decompose the proble…
CALM: Current Aligned Link Manipulation for Single Arm Oversized Object Lifting
Jun Hu, Sihan Chen, Kosta Jovanovic +4
Most robots manipulate objects solely with their end effectors, whereas humans flexibly leverage different body parts, such as the forearm and elbow, especially when handling overs…
Phase-and-First-Arrival VLM Feedback for Sparse-Reward Reinforcement Learning in Surgical Manipulation
Wanli Liuchen, Fangyuan Wang, Bin Li +4
Sparse outcome feedback limits what robots can learn from unsuccessful attempts at complex manipulation. Failed multi-stage surgical attempts can contain grasps, lifts, or transfer…
Dressing in Motion: A Human Motion-Aware Diffusion Policy for Robot-Assisted Dressing
Haoxiang Sun, Fangyuan Wang, Songhao Huang +4
Robotic dressing assistance is a promising solution for supporting older adults with physical impairments in daily living. However, dressing under human motion remains challenging,…
Vision-Based Tactile Intelligence for Robotics: Sensing, Learning, and Embodied Manipulation
Peng Zhou, Jun Hu, Sihan Chen +12
Tactile sensing is essential for robots in contact-rich tasks, yet many tactile sensors still provide sparse, low-dimensional signals that do not capture sufficient information for…
Think Proprioceptively: State-Grounded Visual Token Selection for VLA Policies
Fangyuan Wang, Peng Zhou, Jiaming Qi +4
Vision-language-action (VLA) models typically inject proprioception only as a late conditioning signal, preventing robot state from grounding instruction understanding or directing…
BagIt! An Adaptive Dual-Arm Manipulation of Fabric Bags for Object Bagging
Peng Zhou, Jiaming Qi, Hongmin Wu +3
Bagging tasks, commonly found in industrial scenarios, are challenging considering deformable bags' complicated and unpredictable nature. This paper presents an automated bagging s…
Instruction-Augmented Long-Horizon Planning: Embedding Grounding Mechanisms in Embodied Mobile Manipulation
Fangyuan Wang, Shipeng Lyu, Peng Zhou +3
Enabling humanoid robots to perform long-horizon mobile manipulation planning in real-world environments based on embodied perception and comprehension abilities has been a longsta…
Iterative Shaping of Multi-Particle Aggregates based on Action Trees and VLM
Hoi-Yin Lee, Peng Zhou, Anqing Duan +2
In this paper, we address the problem of manipulating multi-particle aggregates using a bimanual robotic system. Our approach enables the autonomous transport of dispersed particle…
Non-Prehensile Tool-Object Manipulation by Integrating LLM-Based Planning and Manoeuvrability-Driven Controls
Hoi-Yin Lee, Peng Zhou, Anqing Duan +3
The ability to wield tools was once considered exclusive to human intelligence, but it's now known that many other animals, like crows, possess this capability. Yet, robotic system…
Revolutionizing Packaging: A Robotic Bagging Pipeline with Constraint-aware Structure-of-Interest Planning
Jiaming Qi, Peng Zhou, Pai Zheng +4
Bagging operations, common in packaging and assisted living applications, are challenging due to a bag's complex deformable properties. To address this, we develop a robotic system…
Bimanual Deformable Bag Manipulation Using a Structure-of-Interest Based Neural Dynamics Model
Peng Zhou, Pai Zheng, Jiaming Qi +5
The manipulation of deformable objects by robotic systems presents a significant challenge due to their complex and infinite-dimensional configuration spaces. This paper introduces…
Explicit-Implicit Subgoal Planning for Long-Horizon Tasks with Sparse Reward
Fangyuan Wang, Anqing Duan, Peng Zhou +4
The challenges inherent in long-horizon tasks in robotics persist due to the typical inefficient exploration and sparse rewards in traditional reinforcement learning approaches. To…
Integrating Visual Foundation Models for Enhanced Robot Manipulation and Motion Planning: A Layered Approach
Chen Yang, Peng Zhou, Jiaming Qi
This paper presents a novel layered framework that integrates visual foundation models to improve robot manipulation tasks and motion planning. The framework consists of five layer…
Towards Latent Space Based Manipulation of Elastic Rods using Autoencoder Models and Robust Centerline Extractions
Jiaming Qi, Guangfu Ma, Peng Zhou +3
The automatic shape control of deformable objects is a challenging (and currently hot) manipulation problem due to their high-dimensional geometric features and complex physical pr…
Adaptive Shape Servoing of Elastic Rods using Parameterized Regression Features and Auto-Tuning Motion Controls
Jiaming Qi, Guangtao Ran, Bohui Wang +4
The robotic manipulation of deformable linear objects has shown great potential in a wide range of real-world applications. However, it presents many challenges due to the objects'…