Radio SLAM: A Review on Radio-Based Simultaneous Localization and Mapping

Abstract

Simultaneous localization and mapping (SLAM) algorithm has enabled the automation of mobile robots in unknown environments. It enables the robot to navigate through an unknown trajectory by employing sensors that provide measurements to infer the surrounding environment and use this information to localize the robot. Sensor technology plays a key role in defining the quality of measurements as it affects the overall performance of SLAM. While visual sensors, like cameras, can capture rich features of the environment, they, however, fail to work in low-light conditions. On the other hand, radio frequency sensors are invariant to light conditions, however, high-frequency signals such as millimeter wave (mm-wave) are prone to severe channel attenuation, therefore, they are suitable for short-range indoor applications. Despite the high localization accuracy that the mm-wave frequency band has to offer, its shortcomings have limited the amount of research work carried out to enhance the performance of SLAM. Therefore, this paper aims to provide an overview of the recent developments in radio SLAM, with a specific focus on mm-wave enabled localization and SLAM methods. However, some notable research work based on other radio frequency sensors has also been discussed. In addition, we highlight the role of deep learning-based methods for localization and identify some of the key challenges in data-driven implementation.INDEX TERMS Angle-of-arrival (AoA), deep learning, direction-of-arrival (DoA), localization, mm wave, radio SLAM, SLAM, ultra-wideband (UWB).

Indoor Positioning System (IPS) Using Ultra-Wide Bandwidth (UWB)—For Industrial Internet of Things (IIoT)

“…It then trains the model and employs inverse mapping to estimate the location of the user or device. A unique challenge of map construction is that the measurements taken by training are not guaranteed to perform in the same physical space, and the measurements may also be obtained from different devices, resulting in an error [ 113 ]. On the other hand, route planning can play a critical role in determining the effective path to reach the end goal by considering various factors, such as distance, traffic, safety hazards, energy and time constraints, leading to an optimized journey with minimal cost to the device [ 114 , 115 ].…”

A review on positioning techniques of mobile robots

“…Global consistency is achieved by knowing that a previously mapped area has been checked again (loop closure) and by using this information to reduce the drift in the estimates [36]. Among all kinds of SLAM (LiDAR-based SLAM, Radio-based SLAM), visual SLAM (VSLAM) is the key academic research due to its advantages of low price, easy installation, and simple algorithm model [37][38][39].…”

A Comprehensive Review of Direction-of-Arrival Estimation and Localization Approaches in Mixed-Field Sources Scenario

“… The problem of estimating the parameters of mixed signals in multipath environments using 2-D arrays (to estimate the direction for both azimuth and elevation angles), can be presented and solved as a new scenario in future research.  The use of radio-based simultaneous mapping and localization process [165,166] and reconfigurable intelligent surface technology [167,168] may provide efficient solutions for the complex assumptions of this subsection and more specific applications in this area.…”