64 citations · 74 across the 6 of their papers we have counts for
6 papers
Learning Excavation of Rigid Objects with Offline Reinforcement Learning
Shiyu Jin, Zhixian Ye, Liangjun Zhang
Autonomous excavation is a challenging task. The unknown contact dynamics between the excavator bucket and the terrain could easily result in large contact forces and jamming probl…
GOATS: Goal Sampling Adaptation for Scooping with Curriculum Reinforcement Learning
Yaru Niu, Shiyu Jin, Zeqing Zhang +3
In this work, we first formulate the problem of robotic water scooping using goal-conditioned reinforcement learning. This task is particularly challenging due to the complex dynam…
Offline-Online Learning of Deformation Model for Cable Manipulation with Graph Neural Networks
Changhao Wang, Yuyou Zhang, Xiang Zhang +5
Manipulating deformable linear objects by robots has a wide range of applications, e.g., manufacturing and medical surgery. To complete such tasks, an accurate dynamics model for p…
Learning Insertion Primitives with Discrete-Continuous Hybrid Action Space for Robotic Assembly Tasks
Xiang Zhang, Shiyu Jin, Changhao Wang +2
This paper introduces a discrete-continuous action space to learn insertion primitives for robotic assembly tasks. Primitive is a sequence of elementary actions with certain exit c…
Trajectory Optimization for Manipulation of Deformable Objects: Assembly of Belt Drive Units
Shiyu Jin, Diego Romeres, Arvind Ragunathan +2
This paper presents a novel trajectory optimization formulation to solve the robotic assembly of the belt drive unit. Robotic manipulations involving contacts and deformable object…
Contact Pose Identification for Peg-in-Hole Assembly under Uncertainties
Shiyu Jin, Xinghao Zhu, Changhao Wang +1
Peg-in-hole assembly is a challenging contact-rich manipulation task. There is no general solution to identify the relative position and orientation between the peg and the hole. I…