33 citations · 33 across the 13 of their papers we have counts for
17 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…
GeoDistill-Refine: Silhouette-First Geometry Distillation for Annotation-Free Spacecraft Segmentation
Yonglong Zhang, Zongwu Xie, Yang Liu
Foundation segmentation models can provide supervision for spacecraft imagery without manual training masks, but their predictions vary with textual prompts and may contain geometr…
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…
GAP-GDRNet: Geometry-aware monocular 6D pose estimation for spacecraft using synthetic geometric supervision
Zongwu Xie, Yonglong Zhang, Yifan Yang +2
Monocular spacecraft 6D pose estimation remains difficult under weak texture, thin structures, illumination variation, and occlusion. This article presents GAP-GDRNet, a geometry-a…
Precision-Aware Illumination-Disentangled Vision Transformer for Spacecraft 6D Pose Estimation
Zongwu Xie, Yifan Yang, Yonglong Zhang +3
Vision sensors provide a lightweight solution for spacecraft proximity operations, but monocular spacecraft 6D pose estimation remains difficult under illumination variation, specu…
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…
Mars Traversability Prediction: A Multi-modal Self-supervised Approach for Costmap Generation
Zongwu Xie, Kaijie Yun, Yang Liu +2
We present a robust multi-modal framework for predicting traversability costmaps for planetary rovers. Our model fuses camera and LiDAR data to produce a bird's-eye-view (BEV) terr…
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…
Neural-Network-Driven Reward Prediction as a Heuristic: Advancing Q-Learning for Mobile Robot Path Planning
Yiming Ji, Kaijie Yun, Yang Liu +2
Q-learning is a widely used reinforcement learning technique for solving path planning problems. It primarily involves the interaction between an agent and its environment, enablin…
Diffusion as Reasoning: Enhancing Object Navigation via Diffusion Model Conditioned on LLM-based Object-Room Knowledge
Yiming Ji, Kaijie Yun, Yang Liu +4
The Object Navigation (ObjectNav) task aims to guide an agent to locate target objects in unseen environments using partial observations. Prior approaches have employed location pr…
NEDS-SLAM: A Neural Explicit Dense Semantic SLAM Framework using 3D Gaussian Splatting
Yiming Ji, Yang Liu, Guanghu Xie +2
We propose NEDS-SLAM, a dense semantic SLAM system based on 3D Gaussian representation, that enables robust 3D semantic mapping, accurate camera tracking, and high-quality renderin…