4 citations · 6 across the 15 of their papers we have counts for
16 papers
GWAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation
Ke Gui, Chenghao Shi, Ziyue Wang +3
World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies beyond the current field of view,…
GeoLoco: Leveraging 3D Geometric Priors from Visual Foundation Model for Robust RGB-Only Humanoid Locomotion
Yufei Liu, Xieyuanli Chen, Hainan Pan +5
The prevailing paradigm of perceptive humanoid locomotion relies heavily on active depth sensors. However, this depth-centric approach fundamentally discards the rich semantic and…
Efficient Image-Goal Navigation with Representative Latent World Model
Zhiwei Zhang, Hui Zhang, Kaihong Huang +2
World models enable robots to conduct counterfactual reasoning in physical environments by predicting future world states. While conventional approaches often prioritize pixel-leve…
Efficient Multimodal 3D Object Detector via Instance-Level Contrastive Distillation
Zhuoqun Su, Huimin Lu, Shuaifeng Jiao +3
Multimodal 3D object detectors leverage the strengths of both geometry-aware LiDAR point clouds and semantically rich RGB images to enhance detection performance. However, the inhe…
LuSeg: Efficient Negative and Positive Obstacles Segmentation via Contrast-Driven Multi-Modal Feature Fusion on the Lunar
Shuaifeng Jiao, Zhiwen Zeng, Zhuoqun Su +3
As lunar exploration missions grow increasingly complex, ensuring safe and autonomous rover-based surface exploration has become one of the key challenges in lunar exploration task…
BEVDiffLoc: End-to-End LiDAR Global Localization in BEV View based on Diffusion Model
Ziyue Wang, Chenghao Shi, Neng Wang +3
Localization is one of the core parts of modern robotics. Classic localization methods typically follow the retrieve-then-register paradigm, achieving remarkable success. Recently,…
A Novel Decomposed Feature-Oriented Framework for Open-Set Semantic Segmentation on LiDAR Data
Wenbang Deng, Xieyuanli Chen, Qinghua Yu +3
Semantic segmentation is a key technique that enables mobile robots to understand and navigate surrounding environments autonomously. However, most existing works focus on segmenti…
Image-Goal Navigation Using Refined Feature Guidance and Scene Graph Enhancement
Zhicheng Feng, Xieyuanli Chen, Chenghao Shi +4
In this paper, we introduce a novel image-goal navigation approach, named RFSG. Our focus lies in leveraging the fine-grained connections between goals, observations, and the envir…
Flexible Exoskeleton Control Based on Binding Alignment Strategy and Full-arm Coordination Mechanism
Chuang Cheng, Xinglong Zhang, Xieyuanli Chen +6
In rehabilitation, powered, and teleoperation exoskeletons, connecting the human body to the exoskeleton through binding attachments is a common configuration. However, the uncerta…
Leveraging Semantic Graphs for Efficient and Robust LiDAR SLAM
Neng Wang, Huimin Lu, Zhiqiang Zheng +3
Accurate and robust simultaneous localization and mapping (SLAM) is crucial for autonomous mobile systems, typically achieved by leveraging the geometric features of the environmen…
A Novel Multi-Gait Strategy for Stable and Efficient Quadruped Robot Locomotion
Daoxun Zhang, Xieyuanli Chen, Zhengyu Zhong +3
Taking inspiration from the natural gait transition mechanism of quadrupeds, devising a good gait transition strategy is important for quadruped robots to achieve energy-efficient…
NeuroVE: Brain-inspired Linear-Angular Velocity Estimation with Spiking Neural Networks
Xiao Li, Xieyuanli Chen, Ruibin Guo +4
Vision-based ego-velocity estimation is a fundamental problem in robot state estimation. However, the constraints of frame-based cameras, including motion blur and insufficient fra…
SGLC: Semantic Graph-Guided Coarse-Fine-Refine Full Loop Closing for LiDAR SLAM
Neng Wang, Xieyuanli Chen, Chenghao Shi +3
Loop closing is a crucial component in SLAM that helps eliminate accumulated errors through two main steps: loop detection and loop pose correction. The first step determines wheth…
SegNet4D: Efficient Instance-Aware 4D Semantic Segmentation for LiDAR Point Cloud
Neng Wang, Ruibin Guo, Chenghao Shi +5
4D LiDAR semantic segmentation, also referred to as multi-scan semantic segmentation, plays a crucial role in enhancing the environmental understanding capabilities of autonomous v…
Diffusion-Based Point Cloud Super-Resolution for mmWave Radar Data
Kai Luan, Chenghao Shi, Neng Wang +3
The millimeter-wave radar sensor maintains stable performance under adverse environmental conditions, making it a promising solution for all-weather perception tasks, such as outdo…
TSCM: A Teacher-Student Model for Vision Place Recognition Using Cross-Metric Knowledge Distillation
Yehui Shen, Mingmin Liu, Huimin Lu +1
Visual place recognition (VPR) plays a pivotal role in autonomous exploration and navigation of mobile robots within complex outdoor environments. While cost-effective and easily d…