Abstract
This paper deals with Multi-Robot SLAM for large scale map building. Specifically, each robot estimates a local map using EKF, and we merge these local maps into a global map. In this paper, we provide a new RLS based algorithm for map merging. First, we transform local maps into relative information which is considered as measurements for the global map. Then, we update the state estimate by RLS considering the weighting of measurements, which is determined by error propagation from the EKF SLAM. We prove the convergence of the error covariance matrix in this algorithm. In experimental results, we confirm the validity of the proposed algorithm and correctness of derived theorems for the convergence.
| Original language | English |
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| Pages | 164-169 |
| Number of pages | 6 |
| Publication status | Published - 2013 |
| Event | 2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan Duration: 2013 Sept 14 → 2013 Sept 17 |
Other
| Other | 2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 |
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| Country/Territory | Japan |
| City | Nagoya |
| Period | 13/9/14 → 13/9/17 |
Keywords
- EKF SLAM
- Map fusion
- Multi-robot SLAM
- RLS
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering