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Recursive Filtering for Mobile Robot Localization Under an Energy Harvesting Sensor by Yanyang Lu; Bo Shen; Yuxuan Shen is a Engineering article available to read on EtoBox.

What is Recursive Filtering for Mobile Robot Localization Under an Energy Harvesting Sensor about?

## Abstract In this paper, the localization problem of the mobile robot (MR) with an energy harvesting sensor (EHS) is studied. A specific situation is regarded, which is that the MR equips with an EHS who owns the capacity for absorbing the energy from the surroundings. When the sensor energy is sufficient, the sensor can send its measurement to the filter. Otherwise, the sensor energy‐induced measurement missing phenomenon will occur. For the sake of acquiring the measurement missing rate, the relationship between the amount of the sensor energy and its probability distribution is derived recursively at each time instant. The purpose of this paper is to seek out a feasible solution to the addressed MR localization (MRL) problem (MRLP) by devising the desired time‐varying filter. Firstly, in the presence of the sensor energy‐induced measurement missing phenomenon, an upper bound (UB) for the filtering error (FE) covariance (FEC) is acquired recursively. Then, the acquired UB is minimized by characterizing the desired filter gain adequately. Finally, a simulation is conducted to testify the availability of the proposed MRL algorithm (MRLA).

Who reads Recursive Filtering for Mobile Robot Localization Under an Energy Harvesting Sensor?

It is typically read by researchers, students, and practitioners in Engineering.

Author
Yanyang Lu; Bo Shen; Yuxuan Shen
Publisher
Wiley
Published
2021
Language
EN
Field
Engineering (Physical Sciences)

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