Find in Library
Search millions of books, articles, and more
Indexed Open Access Databases
Overview of Multi-Robot Collaborative SLAM from the Perspective of Data Fusion
oleh: Weifeng Chen, Xiyang Wang, Shanping Gao, Guangtao Shang, Chengjun Zhou, Zhenxiong Li, Chonghui Xu, Kai Hu
Format: | Article |
---|---|
Diterbitkan: | MDPI AG 2023-06-01 |
Deskripsi
In the face of large-scale environmental mapping requirements, through the use of lightweight and inexpensive robot groups to perceive the environment, the multi-robot cooperative (V)SLAM scheme can resolve the individual cost, global error accumulation, computational load, and risk concentration problems faced by single-robot SLAM schemes. Such schemes are robust and stable, form a current research hotspot, and relevant algorithms are being updated rapidly. In order to enable the reader to understand the development of this field rapidly and fully, this paper provides a comprehensive review. First, the development history of multi-robot collaborative SLAM is reviewed. Second, the fusion algorithms and architectures are detailed. Third, from the perspective of machine learning classification, the existing algorithms in this field are discussed, including the latest updates. All of this will make it easier for readers to discover problems that need to be studied further. Finally, future research prospects are listed.