A Joint State and Fault Fusion Estimation Scheme for Mobile Robot Localization with Energy Harvesting Sensors

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.