Efficient Localization Using Radio-Based Sensors and Odometry

One of the most important and diverse topics of the modern research landscape is Industry 4.0. Apart from tasks like management of energy or flexible production processes, autonomous industrial robots play a crucial role in this context. Because of the lacking accuracy of global navigation systems in indoor environments, other radio-based methods are required for indoor localization. In this paper, we present a cost-efficient approach that fuses the data of established sensors of autonomous robots with a radio-based method. Signal strength measurements are used for Direction of Arrival estimation, yielding the advantage that no prior information about the environment is required for localizing the object in contrast to the widespread Fingerprinting. The radio-based concept is supported in this work by odometry measurements of the mobile platform. By fusing these information, the concept of a low-cost and powerful localization method is introduced. To allow for an efficient fusion concept, we perform a detailed stochastic characterization of all utilized sensors and motion models. The potential of the localization approach is validated by various differing simulation scenarios and real life measurements.