Recursive fusion estimation for mobile robot localization under multiple energy harvesting sensors

Abstract

This paper is concerned with the recursive fusion estimation-based mobile robot localization (RL) problem by employing multiple energy harvesting sensors (EHSs). In the addressed RL problem, multiple sensors with energy harvesting capacity are deployed to produce measurements used for RL. When the sensors own sufficient energy, the sensors can output measurements and then send them to the corresponding local filter. Otherwise, the sensor energy-induced missing measurement phenomenon will occur. In order to obtain the missing measurement rate, at each time instant, the relationship between the totality of the sensor energy and its probability distribution is derived recursively. This paper aims at seeking out a practicable solution to the addressed mobile RL problem. First, in the presence of the sensor energy-induced measurement missing phenomenon, an upper bound (UB) of the local localization error covariance is recursively acquired. Then, such a derived UB is minimized by suitably devising the desired local filter parameter. Subsequently, the covariance intersection fusion method is adopted to achieve the addressed RL problem. In the end, a simulation is conducted to verify the practicability of the developed RL scheme.