12 citations · 16 across the 9 of their papers we have counts for
9 papers
Lightweight Neural Path Planning
Jinsong Li, Shaochen Wang, Ziyang Chen +2
Learning-based path planning is becoming a promising robot navigation methodology due to its adaptability to various environments. However, the expensive computing and storage asso…
Vision-Based Reactive Planning and Control of Quadruped Robots in Unstructured Dynamic Environments
Tangyu Qian, Zhangli Zhou, Shaocheng Wang +3
Quadruped robots have received increasing attention for the past few years. However, existing works primarily focus on static environments or assume the robot has full observations…
A Nested U-Structure for Instrument Segmentation in Robotic Surgery
Yanjie Xia, Shaochen Wang, Zhen Kan
Robot-assisted surgery has made great progress with the development of medical imaging and robotics technology. Medical scene understanding can greatly improve surgical performance…
TODE-Trans: Transparent Object Depth Estimation with Transformer
Kang Chen, Shaochen Wang, Beihao Xia +3
Transparent objects are widely used in industrial automation and daily life. However, robust visual recognition and perception of transparent objects have always been a major chall…
A Robotic Visual Grasping Design: Rethinking Convolution Neural Network with High-Resolutions
Zhangli Zhou, Shaochen Wang, Ziyang Chen +2
High-resolution representations are important for vision-based robotic grasping problems. Existing works generally encode the input images into low-resolution representations via s…
What You See is What You Grasp: User-Friendly Grasping Guided by Near-eye-tracking
Shaochen Wang, Wei Zhang, Zhangli Zhou +5
This work presents a next-generation human-robot interface that can infer and realize the user's manipulation intention via sight only. Specifically, we develop a system that integ…
When Transformer Meets Robotic Grasping: Exploits Context for Efficient Grasp Detection
Shaochen Wang, Zhangli Zhou, Zhen Kan
In this paper, we present a transformer-based architecture, namely TF-Grasp, for robotic grasp detection. The developed TF-Grasp framework has two elaborate designs making it well…
Context-Based Soft Actor Critic for Environments with Non-stationary Dynamics
Yuan Pu, Shaochen Wang, Xin Yao +1
The performance of deep reinforcement learning methods prone to degenerate when applied to environments with non-stationary dynamics. In this paper, we utilize the latent context r…
Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning
Yuan Pu, Shaochen Wang, Rui Yang +2
Deep reinforcement learning methods have shown great performance on many challenging cooperative multi-agent tasks. Two main promising research directions are multi-agent value fun…