165 citations · 332 across the 61 of their papers we have counts for
12 papers · 1 filter
Learning Monocular Depth from Events via Egomotion Compensation
Haitao Meng, Chonghao Zhong, Sheng Tang +6
Event cameras are neuromorphically inspired sensors that sparsely and asynchronously report brightness changes. Their unique characteristics of high temporal resolution, high dynam…
Gassidy: Gaussian Splatting SLAM in Dynamic Environments
Long Wen, Shixin Li, Yu Zhang +5
3D Gaussian Splatting (3DGS) allows flexible adjustments to scene representation, enabling continuous optimization of scene quality during dense visual simultaneous localization an…
Motion Planning for Robotics: A Review for Sampling-based Planners
Liding Zhang, Kuanqi Cai, Zewei Sun +5
Recent advancements in robotics have transformed industries such as manufacturing, logistics, surgery, and planetary exploration. A key challenge is developing efficient motion pla…
E-3DGS: Gaussian Splatting with Exposure and Motion Events
Xiaoting Yin, Hao Shi, Yuhan Bao +4
Achieving 3D reconstruction from images captured under optimal conditions has been extensively studied in the vision and imaging fields. However, in real-world scenarios, challenge…
LEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks
Kejia Chen, Zheng Shen, Yue Zhang +5
Large Language Models (LLMs) have gained popularity in task planning for long-horizon manipulation tasks. To enhance the validity of LLM-generated plans, visual demonstrations and…
TacDiffusion: Force-domain Diffusion Policy for Precise Tactile Manipulation
Yansong Wu, Zongxie Chen, Fan Wu +6
Assembly is a crucial skill for robots in both modern manufacturing and service robotics. However, mastering transferable insertion skills that can handle a variety of high-precisi…
Learning effective pruning at initialization from iterative pruning
Shengkai Liu, Yaofeng Cheng, Fusheng Zha +4
Pruning at initialization (PaI) reduces training costs by removing weights before training, which becomes increasingly crucial with the growing network size. However, current PaI m…
Locomotion Generation for a Rat Robot based on Environmental Changes via Reinforcement Learning
Xinhui Shan, Yuhong Huang, Zhenshan Bing +4
This research focuses on developing reinforcement learning approaches for the locomotion generation of small-size quadruped robots. The rat robot NeRmo is employed as the experimen…
Real-Time Adaptive Safety-Critical Control with Gaussian Processes in High-Order Uncertain Models
Yu Zhang, Long Wen, Xiangtong Yao +4
This paper presents an adaptive online learning framework for systems with uncertain parameters to ensure safety-critical control in non-stationary environments. Our approach consi…
Optimizing Dynamic Balance in a Rat Robot via the Lateral Flexion of a Soft Actuated Spine
Yuhong Huang, Zhenshan Bing, Zitao Zhang +3
Balancing oneself using the spine is a physiological alignment of the body posture in the most efficient manner by the muscular forces for mammals. For this reason, we can see many…
Online Efficient Safety-Critical Control for Mobile Robots in Unknown Dynamic Multi-Obstacle Environments
Yu Zhang, Guangyao Tian, Long Wen +5
This paper proposes a LiDAR-based goal-seeking and exploration framework, addressing the efficiency of online obstacle avoidance in unstructured environments populated with static…
Real-time Contact State Estimation in Shape Control of Deformable Linear Objects under Small Environmental Constraints
Kejia Chen, Zhenshan Bing, Yansong Wu +4
Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust…