CoSAR: Multi-Robot Collaborative Semantic Mapping over Wireless Networks

Kai Hu1; Lei Zhan1; Longhao Zou2; Yi Han3; Ting Bi4; Gabriel-Miro Muntean5

10.1109/BMSB58369.2023.10211095

2023

2155-5044

979-8-3503-2153-1

2023 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

2023-June

1-6

14-16 June 2023

Beijing, China

The recent advancements in 3D-rich media interactive technologies, including Augmented Reality (AR) and Extended Reality (XR), have brought about a significant proliferation of applications in various industries. In response to this trend, multi-robot collaborative semantic mapping has emerged as a promising approach to improve the accuracy and speed of large-scale environment perception for intelligent robotic systems. This paper proposes a framework that utilizes cooperative self-adaptation-based wireless communication between the server and robotic agents (CoSAR) to enhance the efficiency of semantic mapping in large-scale environments. Integrating this adaptive wireless communication reduces the time required for mapping, and each robot’s CPU and memory utilization is effectively decreased. Simultaneously, dynamic object removal and global map optimization are executed based on semantic segmentation information, resulting in enhanced accuracy and robustness of the semantic octo-tree map. The framework has been validated and tested on publicly available datasets using network simulations and deployed on real robots for real-life operations.

collaborative multi-robot system semantic mapping self-adaptation edge computing large-scale environment perception

第一

EI

20233614670661

Augmented reality ; Collaborative robots ; Cooperative communication ; Edge computing ; Industrial robots ; Intelligent robots ; Mapping ; Robot learning ; Semantics

Surveying:405.3 ; Data Communication, Equipment and Techniques:722.3 ; Digital Computers and Systems:722.4 ; Computer Software, Data Handling and Applications:723 ; Robotics:731.5 ; Robot Applications:731.6

IEEE

1.Institue of Future Networks, Southern University of Science and Technology, Shenzhen, China
2.Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China
3.School of Information Engineering, Wuhan University of Technology, Wuhan, China
4.School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, China
5.School of Electronic Engineering, Dublin City University, Dublin, Ireland

Kai Hu,Lei Zhan,Longhao Zou,et al. CoSAR: Multi-Robot Collaborative Semantic Mapping over Wireless Networks[C],2023:1-6.