24 citations · 29 across the 8 of their papers we have counts for
9 papers
A Dataset and Benchmark for Robotic Cloth Unfolding Grasp Selection: The ICRA 2024 Cloth Competition
Victor-Louis De Gusseme, Thomas Lips, Remko Proesmans +59
Robotic cloth manipulation suffers from a lack of standardized benchmarks and shared datasets for evaluating and comparing different approaches. To address this, we created a bench…
EROAM: Event-based Camera Rotational Odometry and Mapping in Real-time
Wanli Xing, Shijie Lin, Linhan Yang +6
This paper presents EROAM, a novel event-based rotational odometry and mapping system that achieves real-time, accurate camera rotation estimation. Unlike existing approaches that…
One Fling to Goal: Environment-aware Dynamics for Goal-conditioned Fabric Flinging
Linhan Yang, Lei Yang, Haoran Sun +5
Fabric manipulation dynamically is commonly seen in manufacturing and domestic settings. While dynamically manipulating a fabric piece to reach a target state is highly efficient,…
CafkNet: GNN-Empowered Forward Kinematic Modeling for Cable-Driven Parallel Robots
Zeqing Zhang, Linhan Yang, Cong Sun +2
Cable-driven parallel robots (CDPRs) have gained significant attention due to their promising advantages. When deploying CDPRs in practice, the kinematic modeling is a key question…
TacGNN:Learning Tactile-based In-hand Manipulation with a Blind Robot
Linhan Yang, Bidan Huang, Qingbiao Li +4
In this paper, we propose a novel framework for tactile-based dexterous manipulation learning with a blind anthropomorphic robotic hand, i.e. without visual sensing. First, object-…
Learning-based Optoelectronically Innervated Tactile Finger for Rigid-Soft Interactive Grasping
Linhan Yang, Xudong Han, Weijie Guo +3
This paper presents a novel design of a soft tactile finger with omni-directional adaptation using multi-channel optical fibers for rigid-soft interactive grasping. Machine learnin…
Design of an Optoelectronically Innervated Gripper for Rigid-Soft Interactive Grasping
Linhan Yang, Xudong Han, Weijie Guo +4
Over the past few decades, efforts have been made towards robust robotic grasping, and therefore dexterous manipulation. The soft gripper has shown their potential in robust graspi…
DeepClaw: A Robotic Hardware Benchmarking Platform for Learning Object Manipulation
Fang Wan, Haokun Wang, Xiaobo Liu +2
We present DeepClaw as a reconfigurable benchmark of robotic hardware and task hierarchy for robot learning. The DeepClaw benchmark aims at a mechatronics perspective of the robot…
Rigid-Soft Interactive Learning for Robust Grasping
Linhan Yang, Fang Wan, Haokun Wang +4
Inspired by widely used soft fingers on grasping, we propose a method of rigid-soft interactive learning, aiming at reducing the time of data collection. In this paper, we classify…