1 code implementation • 23 Feb 2024 • Kechun Xu, Zhongxiang Zhou, Jun Wu, Haojian Lu, Rong Xiong, Yue Wang
For the inner loop, we learn an active seeing policy for self-confident object matching to improve the perception of place.
no code implementations • 6 Apr 2023 • Zhixuan Xu, Kechun Xu, Yue Wang, Rong Xiong
We focus on the task of language-conditioned object placement, in which a robot should generate placements that satisfy all the spatial relational constraints in language instructions.
1 code implementation • 17 Jul 2022 • Zizhang Li, Mengmeng Wang, Huaijin Pi, Kechun Xu, Jianbiao Mei, Yong liu
However, the redundant parameters within the network structure can cause a large model size when scaling up for desirable performance.
Ranked #4 on Video Reconstruction on UVG
1 code implementation • 9 May 2022 • Liang Xie, Hongxiang Yu, Kechun Xu, Tong Yang, Minhang Wang, Haojian Lu, Rong Xiong, Yue Wang
This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary unseen shapes in real world with minimal sim-to-real cost.
1 code implementation • 9 Mar 2021 • Kechun Xu, Hongxiang Yu, Qianen Lai, Yue Wang, Rong Xiong
In this paper, a goal-conditioned hierarchical reinforcement learning formulation with high sample efficiency is proposed to learn a push-grasping policy for grasping a specific object in clutter.
Hierarchical Reinforcement Learning Robotics