1 citations · 2 across the 9 of their papers we have counts for
12 papers
GCS-Bridging: Restoring Connectivity of Disconnected Convex Sets for Graph-of-Convex-Sets Motion Planning
Xiaokai Zhou, Baoshi Cao, Yang Liu +4
Graph-of-Convex-Sets (GCS)-based trajectory optimization represents collision-free regions in configuration space as a finite collection of convex sets and directly performs collis…
HCPG-Flow:Hierarchical Contact-Progress Guidance for Flow-Policy Robot Manipulation
Guanghu Xie, Mingxu Li, Shuo Zhang +5
Flow policies can represent multimodal action distributions for robot manipulation, yet a robot must execute one action at each control step. When several proposals are sampled, cr…
Component-Aware Structure-Preserving Style Transfer for Satellite Visual Sim2Real Data Construction
Zongwu Xie, Yonglong Zhang, Yifan Yang +3
For camera-based satellite visual sensing, Sim2Real data construction requires images that approach real-domain sensor appearance while retaining the annotations inherited from sim…
Now You See That: Learning End-to-End Humanoid Locomotion from Raw Pixels
Wandong Sun, Yongbo Su, Leoric Huang +10
Achieving robust vision-based humanoid locomotion remains challenging due to two fundamental issues: the sim-to-real gap introduces significant perception noise that degrades perfo…
HDCNet: A Hybrid Depth Completion Network for Grasping Transparent and Reflective Objects
Guanghu Xie, Mingxu Li, Songwei Wu +4
Depth perception of transparent and reflective objects has long been a critical challenge in robotic manipulation.Conventional depth sensors often fail to provide reliable measurem…
ULC: A Unified and Fine-Grained Controller for Humanoid Loco-Manipulation
Wandong Sun, Luying Feng, Baoshi Cao +3
Loco-Manipulation for humanoid robots aims to enable robots to integrate mobility with upper-body tracking capabilities. Most existing approaches adopt hierarchical architectures t…
DCIRNet: Depth Completion with Iterative Refinement for Dexterous Grasping of Transparent and Reflective Objects
Guanghu Xie, Zhiduo Jiang, Yonglong Zhang +4
Transparent and reflective objects in everyday environments pose significant challenges for depth sensors due to their unique visual properties, such as specular reflections and li…
HTMNet: A Hybrid Network with Transformer-Mamba Bottleneck Multimodal Fusion for Transparent and Reflective Objects Depth Completion
Guanghu Xie, Yonglong Zhang, Zhiduo Jiang +4
Transparent and reflective objects pose significant challenges for depth sensors, resulting in incomplete depth information that adversely affects downstream robotic perception and…
Learning Perceptive Humanoid Locomotion over Challenging Terrain
Wandong Sun, Baoshi Cao, Long Chen +4
Humanoid robots are engineered to navigate terrains akin to those encountered by humans, which necessitates human-like locomotion and perceptual abilities. Currently, the most reli…
Learning Humanoid Locomotion with World Model Reconstruction
Wandong Sun, Long Chen, Yongbo Su +3
Humanoid robots are designed to navigate environments accessible to humans using their legs. However, classical research has primarily focused on controlled laboratory settings, re…
NNPP: A Learning-Based Heuristic Model for Accelerating Optimal Path Planning on Uneven Terrain
Yiming Ji, Yang Liu, Guanghu Xie +3
Intelligent autonomous path planning is essential for enhancing the exploration efficiency of mobile robots operating in uneven terrains like planetary surfaces and off-road enviro…
Prototype Design and Efficiency Analysis of a Novel Robot Drive Based on 3K-H-V Topology
Le Qi, Dapeng Yang, Baoshi Cao +4
Robot actuators directly affect the performance of robots, and robot drives directly affect the performance of robot actuators. With the development of robotics, robots have put hi…