特異環境を考慮したLRFマップマッチングとオドメトリのMHE融合に基づく移動ロボットの自己位置推定 [in Japanese] Mobile Robot Localization Integrating LRF Map-matching and Odometry Based on Moving Horizon Estimation Considering Singular Environments [in Japanese]
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In this paper, we propose a localization method integrating laser range finder (LRF) measurement and odometry by moving horizon estimation (MHE). The position and the attitude angle of a robot are estimated by solving an optimization problem using multiple sampling data while shifting the evaluation interval at each sampling. The relative importance of the estimations of LRF and odometry are balanced by adapting to the number of LRF measurements. With the proposed method, accurate localization can be realized even in singular environments where the self-pose cannot be localized using only LRF measurements. The accuracy of the proposed method is verified through comparisons with conventional methods on numerical simulations. In addition, we verify the robustness and feasibility of the proposed method for singular environments through numerical simulations and experiments.
- Transactions of the Society of Instrument and Control Engineers
Transactions of the Society of Instrument and Control Engineers 53(6), 355-365, 2017
The Society of Instrument and Control Engineers