3 citations · 13 across the 22 of their papers we have counts for
22 papers
BiRoAD: Learning Shared and Role-Adaptive Representations for Bimanual Manipulation
Yan Shen, Yuchen Liu, Feng Jiang +5
Bimanual manipulation requires policies that coordinate two arms while adapting their functional roles to scene geometry, object configuration, and task context. Learning such scen…
Scaling Manual-Grounded Appliance Manipulation with Data Synthesis and Unified Planning
Yuxing Long, Lei Kang, Ziyan Yu +8
Operating household appliances requires long-horizon planning that is state-dependent and robust to disturbances, yet existing large models fall short, as no sufficiently diverse,…
LaST-HD: Learning Latent Physical Reasoning from Scalable Human Data for Robot Manipulation
Jiaming Liu, Yinxi Wang, Chenyang Gu +15
Human-hand demonstrations provide a direct and scalable source of physical interaction data for robot learning. While manual retargeting is indispensable for establishing kinematic…
AT-VLA: Adaptive Tactile Injection for Enhanced Feedback Reaction in Vision-Language-Action Models
Xiaoqi Li, Muhe Cai, Jiadong Xu +5
Vision-Language-Action (VLA) models have significantly advanced the capabilities of robotic agents in executing diverse tasks; however, they still face challenges in contact-rich m…
BiPreManip: Learning Affordance-Based Bimanual Preparatory Manipulation through Anticipatory Collaboration
Yan Shen, Feng Jiang, Zichen He +5
Many everyday objects are difficult to directly grasp (e.g., a flat iPad) or manipulate functionally (e.g., opening the cap of a pen lying on a desk). Such tasks require sequential…
AnchorVLA4D: an Anchor-Based Spatial-Temporal Vision-Language-Action Model for Robotic Manipulation
Juan Zhu, Zhanying Shao, Xiaoqi Li +4
Since current Vision-Language-Action (VLA) systems suffer from limited spatial perception and the absence of memory throughout manipulation, we investigate visual anchors as a mean…
Real2Edit2Real: Generating Robotic Demonstrations via a 3D Control Interface
Yujie Zhao, Hongwei Fan, Di Chen +5
Recent progress in robot learning has been driven by large-scale datasets and powerful visuomotor policy architectures, yet policy robustness remains limited by the substantial cos…
Imagine2Act: Leveraging Object-Action Motion Consistency from Imagined Goals for Robotic Manipulation
Liang Heng, Jiadong Xu, Yiwen Wang +6
Relational object rearrangement (ROR) tasks (e.g., insert flower to vase) require a robot to manipulate objects with precise semantic and geometric reasoning. Existing approaches e…
SR3D: Unleashing Single-view 3D Reconstruction for Transparent and Specular Object Grasping
Mingxu Zhang, Xiaoqi Li, Jiahui Xu +5
Recent advancements in 3D robotic manipulation have improved grasping of everyday objects, but transparent and specular materials remain challenging due to depth sensing limitation…
BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assembly
Yan Shen, Ruihai Wu, Yubin Ke +6
Shape assembly, the process of combining parts into a complete whole, is a crucial robotic skill with broad real-world applications. Among various assembly tasks, geometric assembl…
CrayonRobo: Object-Centric Prompt-Driven Vision-Language-Action Model for Robotic Manipulation
Xiaoqi Li, Lingyun Xu, Mingxu Zhang +8
In robotic, task goals can be conveyed through various modalities, such as language, goal images, and goal videos. However, natural language can be ambiguous, while images or video…
3DWG: 3D Weakly Supervised Visual Grounding via Category and Instance-Level Alignment
Xiaoqi Li, Jiaming Liu, Nuowei Han +4
The 3D weakly-supervised visual grounding task aims to localize oriented 3D boxes in point clouds based on natural language descriptions without requiring annotations to guide mode…
ManipGPT: Is Affordance Segmentation by Large Vision Models Enough for Articulated Object Manipulation?
Taewhan Kim, Hojin Bae, Zeming Li +4
Visual actionable affordance has emerged as a transformative approach in robotics, focusing on perceiving interaction areas prior to manipulation. Traditional methods rely on pixel…
Human-centered In-building Embodied Delivery Benchmark
Zhuoqun Xu, Yang Liu, Xiaoqi Li +2
Recently, the concept of embodied intelligence has been widely accepted and popularized, leading people to naturally consider the potential for commercialization in this field. In…
SpatialBot: Precise Spatial Understanding with Vision Language Models
Wenxiao Cai, Iaroslav Ponomarenko, Jianhao Yuan +4
Vision Language Models (VLMs) have achieved impressive performance in 2D image understanding, however they are still struggling with spatial understanding which is the foundation o…
AIC MLLM: Autonomous Interactive Correction MLLM for Robust Robotic Manipulation
Chuyan Xiong, Chengyu Shen, Xiaoqi Li +4
The ability to reflect on and correct failures is crucial for robotic systems to interact stably with real-life objects.Observing the generalization and reasoning capabilities of M…
NaturalVLM: Leveraging Fine-grained Natural Language for Affordance-Guided Visual Manipulation
Ran Xu, Yan Shen, Xiaoqi Li +2
Enabling home-assistant robots to perceive and manipulate a diverse range of 3D objects based on human language instructions is a pivotal challenge. Prior research has predominantl…
ManipVQA: Injecting Robotic Affordance and Physically Grounded Information into Multi-Modal Large Language Models
Siyuan Huang, Iaroslav Ponomarenko, Zhengkai Jiang +5
While the integration of Multi-modal Large Language Models (MLLMs) with robotic systems has significantly improved robots' ability to understand and execute natural language instru…
ManipLLM: Embodied Multimodal Large Language Model for Object-Centric Robotic Manipulation
Xiaoqi Li, Mingxu Zhang, Yiran Geng +6
Robot manipulation relies on accurately predicting contact points and end-effector directions to ensure successful operation. However, learning-based robot manipulation, trained on…
ImageManip: Image-based Robotic Manipulation with Affordance-guided Next View Selection
Xiaoqi Li, Yanzi Wang, Yan Shen +6
In the realm of future home-assistant robots, 3D articulated object manipulation is essential for enabling robots to interact with their environment. Many existing studies make use…
RGBManip: Monocular Image-based Robotic Manipulation through Active Object Pose Estimation
Boshi An, Yiran Geng, Kai Chen +3
Robotic manipulation requires accurate perception of the environment, which poses a significant challenge due to its inherent complexity and constantly changing nature. In this con…
Discuss Before Moving: Visual Language Navigation via Multi-expert Discussions
Yuxing Long, Xiaoqi Li, Wenzhe Cai +1
Visual language navigation (VLN) is an embodied task demanding a wide range of skills encompassing understanding, perception, and planning. For such a multifaceted challenge, previ…