[1]WANG Hebin,GE Quanbo,LIU Huaping,et al.Multi-robot active SLAM for observation fusion and attractor[J].CAAI Transactions on Intelligent Systems,2021,16(2):371-377.[doi:10.11992/tis.202006019]
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Multi-robot active SLAM for observation fusion and attractor

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 16 Number of periods: 2021 2 Page number: 371-377 Column: 吴文俊人工智能科学技术奖论坛 Public date: 2021-03-05
Title:
Multi-robot active SLAM for observation fusion and attractor
Author(s):
WANG Hebin1;  GE Quanbo2;  LIU Huaping3;  YUAN Xiaohu4
1. School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China;
2. School of Electronics and Information Engineering, Tongji University, Shanghai 201804, China;
3. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China;
4. Department of Automation, Tsinghua University, Beijing 100084, China
Keywords:
active simultaneous location and mapping; multi-robot cooperation; attractor; convex combination fusion; extended Kalman filter; optimal control; mutual information; multi-objective optimization
CLC:
TP510.80
DOI:
10.11992/tis.202006019
Abstract:
Because multi-robot active SLAM cannot fully traverse an environment, and the localization accuracy is not ideal in an unknown environment, a new multi-robot active SLAM algorithm is proposed in this paper. By introducing attractors to enhance communication between multi-robot systems, the accuracy of robot localization and mapping is enhanced, and multi-robot teams are guided to explore the environment. When the same landmark is observed by multiple robots, convex combination fusion is used to fuse the estimate of the landmark by each robot, thereby reducing the uncertainty of the landmark. The simulation results show that the proposed algorithm can cover and traverse the environment and improve the localization accuracy of landmark estimation.
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