A joint state and fault fusion estimation scheme for mobile robot localization with energy harvesting sensors AITranslate
Abstract AITranslate
This study addresses the joint state and fault fusion estimation problem for mobile robot localization under the energy-harvesting sensors. Under such a circumstance, the sensors can harvest energy from the external environment and then consume an amount of energy when transmitting measurements to the corresponding estimator. Based on the energy harvesting mechanism's probability distribution, the probability of measurement loss is computed at each step. The main objective of this study is to tackle the mobile robot localization problem by designing local estimators for each sensor node, where the upper bound of the local estimation error covariance is guaranteed and then minimized by appropriately tuning the estimator parameters. Furthermore, the local estimates are fused using the covariance intersection (CI) fusion approach. Finally, a numerical experiment is presented to demonstrate the effectiveness of the proposed fusion estimation algorithm.
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Basic Information:
DOI:10.23919/CHAIN.2025.000005
Chinese Library Classification Number:
Citation Information:
This study addresses the joint state and fault fusion estimation problem for mobile robot localization under the energy-harvesting sensors. Under such a circumstance, the sensors can harvest energy from the external environment and then consume an amount of energy when transmitting measurements to the corresponding estimator. Based on the energy harvesting mechanism's probability distribution, the probability of measurement loss is computed at each step. The main objective of this study is to tackle the mobile robot localization problem by designing local estimators for each sensor node, where the upper bound of the local estimation error covariance is guaranteed and then minimized by appropriately tuning the estimator parameters. Furthermore, the local estimates are fused using the covariance intersection (CI) fusion approach. Finally, a numerical experiment is presented to demonstrate the effectiveness of the proposed fusion estimation algorithm.
quote
| GB/T 7714-2015 | [1] Ruifeng Gao, Qingchi Qi, Peng Mei, et al. A joint state and fault fusion estimation scheme for mobile robot localization with energy harvesting sensors[J]. Chain, 2025, 2(1): 57-71. DOI:10.23919/CHAIN.2025.000005. |
| MLA | [1] Ruifeng Gao, et al., "A joint state and fault fusion estimation scheme for mobile robot localization with energy harvesting sensors." Chain, vol. 2, no. 1, 2025, pp. 57-71, https://doi.org/10.23919/CHAIN.2025.000005. |
| APA | [1] Ruifeng Gao, Qingchi Qi, Peng Mei, & Cong Huang. (2025). A joint state and fault fusion estimation scheme for mobile robot localization with energy harvesting sensors. Chain, 2(1), 57-71. https://doi.org/10.23919/CHAIN.2025.000005 |
| IEEE | [1] Ruifeng Gao, Qingchi Qi, Peng Mei, and Cong Huang, "A joint state and fault fusion estimation scheme for mobile robot localization with energy harvesting sensors," Chain, vol. 2, no. 1, pp. 57-71, 2025, doi: 10.23919/CHAIN.2025.000005. keywords: {energy harvesting sensors;state and fault estimation;mobile robot localization;fusion estimation} |
