3 citations · 9 across the 8 of their papers we have counts for
9 papers
Generative Artificial Intelligence in Robotic Manipulation: A Survey
Kun Zhang, Peng Yun, Jun Cen +11
This survey provides a comprehensive review on recent advancements of generative learning models in robotic manipulation, addressing key challenges in the field. Robotic manipulati…
Flipbot: Learning Continuous Paper Flipping via Coarse-to-Fine Exteroceptive-Proprioceptive Exploration
Chao Zhao, Chunli Jiang, Junhao Cai +3
This paper tackles the task of singulating and grasping paper-like deformable objects. We refer to such tasks as paper-flipping. In contrast to manipulating deformable objects that…
Learn to Grasp via Intention Discovery and its Application to Challenging Clutter
Chao Zhao, Chunli Jiang, Junhao Cai +3
Humans excel in grasping objects through diverse and robust policies, many of which are so probabilistically rare that exploration-based learning methods hardly observe and learn.…
ERRA: An Embodied Representation and Reasoning Architecture for Long-horizon Language-conditioned Manipulation Tasks
Chao Zhao, Shuai Yuan, Chunli Jiang +4
This letter introduces ERRA, an embodied learning architecture that enables robots to jointly obtain three fundamental capabilities (reasoning, planning, and interaction) for solvi…
Volumetric-based Contact Point Detection for 7-DoF Grasping
Junhao Cai, Jingcheng Su, Zida Zhou +3
In this paper, we propose a novel grasp pipeline based on contact point detection on the truncated signed distance function (TSDF) volume to achieve closed-loop 7-degree-of-freedom…
Open-world Semantic Segmentation for LIDAR Point Clouds
Jun Cen, Peng Yun, Shiwei Zhang +5
Current methods for LIDAR semantic segmentation are not robust enough for real-world applications, e.g., autonomous driving, since it is closed-set and static. The closed-set assum…
Open-set 3D Object Detection
Jun Cen, Peng Yun, Junhao Cai +2
3D object detection has been wildly studied in recent years, especially for robot perception systems. However, existing 3D object detection is under a closed-set condition, meaning…
Deep Metric Learning for Open World Semantic Segmentation
Jun Cen, Peng Yun, Junhao Cai +2
Classical close-set semantic segmentation networks have limited ability to detect out-of-distribution (OOD) objects, which is important for safety-critical applications such as aut…
MetaGrasp: Data Efficient Grasping by Affordance Interpreter Network
Junhao Cai, Hui Cheng, Zhanpeng Zhang +1
Data-driven approach for grasping shows significant advance recently. But these approaches usually require much training data. To increase the efficiency of grasping data collectio…