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20232026
most citedMap++: Towards User-Participatory Visual SLAM Systems with Efficient Map Expansion and Sharing

11 citations · 29 across the 42 of their papers we have counts for

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12 papers · 1 filter

cs.CV2024★ 11 cited

Map++: Towards User-Participatory Visual SLAM Systems with Efficient Map Expansion and Sharing

Xinran Zhang, Hanqi Zhu, Yifan Duan +5

Constructing precise 3D maps is crucial for the development of future map-based systems such as self-driving and navigation. However, generating these maps in complex environments,…

cs.RO2024

MSGField: A Unified Scene Representation Integrating Motion, Semantics, and Geometry for Robotic Manipulation

Yu Sheng, Runfeng Lin, Lidian Wang +5

Combining accurate geometry with rich semantics has been proven to be highly effective for language-guided robotic manipulation. Existing methods for dynamic scenes either fail to…

cs.RO2024

CELLmap: Enhancing LiDAR SLAM through Elastic and Lightweight Spherical Map Representation

Yifan Duan, Xinran Zhang, Yao Li +4

SLAM is a fundamental capability of unmanned systems, with LiDAR-based SLAM gaining widespread adoption due to its high precision. Current SLAM systems can achieve centimeter-level…

cs.RO2024

MHRC: Closed-loop Decentralized Multi-Heterogeneous Robot Collaboration with Large Language Models

Wenhao Yu, Jie Peng, Yueliang Ying +3

The integration of large language models (LLMs) with robotics has significantly advanced robots' abilities in perception, cognition, and task planning. The use of natural language…

cs.CV2024★ 1 cited

LFP: Efficient and Accurate End-to-End Lane-Level Planning via Camera-LiDAR Fusion

Guoliang You, Xiaomeng Chu, Yifan Duan +4

Multi-modal systems enhance performance in autonomous driving but face inefficiencies due to indiscriminate processing within each modality. Additionally, the independent feature l…

cs.RO2024

LDP: A Local Diffusion Planner for Efficient Robot Navigation and Collision Avoidance

Wenhao Yu, Jie Peng, Huanyu Yang +4

The conditional diffusion model has been demonstrated as an efficient tool for learning robot policies, owing to its advancement to accurately model the conditional distribution of…

cs.CV2024

Perception Helps Planning: Facilitating Multi-Stage Lane-Level Integration via Double-Edge Structures

Guoliang You, Xiaomeng Chu, Yifan Duan +6

When planning for autonomous driving, it is crucial to consider essential traffic elements such as lanes, intersections, traffic regulations, and dynamic agents. However, they are…

cs.RO2024

Rotation Initialization and Stepwise Refinement for Universal LiDAR Calibration

Yifan Duan, Xinran Zhang, Guoliang You +8

Autonomous systems often employ multiple LiDARs to leverage the integrated advantages, enhancing perception and robustness. The most critical prerequisite under this setting is the…

cs.RO2024★ 1 cited

Rendering-Enhanced Automatic Image-to-Point Cloud Registration for Roadside Scenes

Yu Sheng, Lu Zhang, Xingchen Li +4

Prior point cloud provides 3D environmental context, which enhances the capabilities of monocular camera in downstream vision tasks, such as 3D object detection, via data fusion. H…

cs.RO2024★ 1 cited

MM-Gaussian: 3D Gaussian-based Multi-modal Fusion for Localization and Reconstruction in Unbounded Scenes

Chenyang Wu, Yifan Duan, Xinran Zhang +3

Localization and mapping are critical tasks for various applications such as autonomous vehicles and robotics. The challenges posed by outdoor environments present particular compl…

cs.CV2024

CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks

Beibei Wang, Zijian Yu, Lu Zhang +8

Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems research and development. However, it…

cs.RO2024

CRPlace: Camera-Radar Fusion with BEV Representation for Place Recognition

Shaowei Fu, Yifan Duan, Yao Li +4

The integration of complementary characteristics from camera and radar data has emerged as an effective approach in 3D object detection. However, such fusion-based methods remain u…