8 papers
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…