1 citations · 1 across the 7 of their papers we have counts for
7 papers
RoCo Challenge at AAAI 2026: Benchmarking Robotic Collaborative Manipulation for Assembly Towards Industrial Automation
Haichao Liu, Yuheng Zhou, Zhenyu Wu +14
Embodied Artificial Intelligence (EAI) is rapidly developing, gradually subverting previous autonomous systems' paradigms from isolated perception to integrated, continuous action.…
CAD-Prompted SAM3: Geometry-Conditioned Instance Segmentation for Industrial Objects
Zhenran Tang, Rohan Nagabhirava, Changliu Liu
Verbal-prompted segmentation is inherently limited by the expressiveness of natural language and struggles with uncommon, instance-specific, or difficult-to-describe objects: scena…
Enhancing Certifiable Semantic Robustness via Robust Pruning of Deep Neural Networks
Hanjiang Hu, Bowei Li, Ziwei Wang +4
Deep neural networks have been widely adopted in many vision and robotics applications with visual inputs. It is essential to verify its robustness against semantic transformation…
Certifying Robustness of Learning-Based Keypoint Detection and Pose Estimation Methods
Xusheng Luo, Tianhao Wei, Simin Liu +6
This work addresses the certification of the local robustness of vision-based two-stage 6D object pose estimation. The two-stage method for object pose estimation achieves superior…
ManiGaussian: Dynamic Gaussian Splatting for Multi-task Robotic Manipulation
Guanxing Lu, Shiyi Zhang, Ziwei Wang +3
Performing language-conditioned robotic manipulation tasks in unstructured environments is highly demanded for general intelligent robots. Conventional robotic manipulation methods…
StableLego: Stability Analysis of Block Stacking Assembly
Ruixuan Liu, Kangle Deng, Ziwei Wang +1
Structural stability is a necessary condition for successful construction of an assembly. However, designing a stable assembly requires a non-trivial effort since a slight variatio…
ThinkBot: Embodied Instruction Following with Thought Chain Reasoning
Guanxing Lu, Ziwei Wang, Changliu Liu +2
Embodied Instruction Following (EIF) requires agents to complete human instruction by interacting objects in complicated surrounding environments. Conventional methods directly con…