MOSAIC: Simultaneous Localization and Environment Mapping using mmWave without a-priori Knowledge

Yassin, Ali; Nasser, Youssef; Al-Dubai, Ahmed; Awad, Mariette

Abstract

Simultaneous Localization and environment mapping (SLAM) is the core to robotic mapping and navigation as it constructs simultaneously the unknown environment and localizes the agent within. However, in millimeter wave (mmWave) research, SLAM is still at its infancy. In this paper, we introduce MOSAIC a new approach for SLAM in indoor environment by exploiting the map-based channel model. More precisely, we perform localization and environment inference through obstacle detection and dimensioning. The concept of Virtual Anchor Nodes (VANs), known in literature as the mirrors of the real anchors with respect to the obstacles in the environment, is firstly introduced. Then, based on these VANs, the obstacles positions
and dimensions are estimated by detecting the zone of paths
obstruction, points of reflection and obstacle vertices estimation.
Cramer-Rao Lower Bounds (CRLB) are then derived to find the optimal number of anchor nodes and measurements points that improve the localization and mapping accuracy. Simulation results have shown high localization accuracy and obstacle detection in different environments using mmWave technology.

Citation

Yassin, A., Nasser, Y., Al-Dubai, A., & Awad, M. (2018). MOSAIC: Simultaneous Localization and Environment Mapping using mmWave without a-priori Knowledge. IEEE Access, 6, 68932-68947. https://doi.org/10.1109/access.2018.2879436

• Journal Article Type: Article
• Acceptance Date: Oct 18, 2018
• Online Publication Date: Nov 9, 2018
• Publication Date: 2018
• Deposit Date: Oct 18, 2018
• Publicly Available Date: Oct 18, 2018
• Journal: IEEE Access
• Electronic ISSN: 2169-3536
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 6
• Pages: 68932-68947
• DOI: https://doi.org/10.1109/access.2018.2879436
• Public URL: http://researchrepository.napier.ac.uk/Output/1319058