# A Review of Mobile Mapping Systems: From Sensors to Applications

arXiv: https://arxiv.org/abs/2205.15865 · HTML: https://mlsanity.com/paper/2205.15865/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 162 references that are in the map.
- First posted on arXiv 31 May 2022.

## Builds on (most cited first, 9 of 9)

- [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://mlsanity.com/paper/1704.04861/) (2017)
- [Benchmarking Single Image Dehazing and Beyond](https://mlsanity.com/paper/1712.04143/) (2017)
- [Lidar for Autonomous Driving: The principles, challenges, and trends for automotive lidar and perception systems](https://mlsanity.com/paper/2004.08467/) (2020)
- [SuMa++: Efficient LiDAR-based Semantic SLAM](https://mlsanity.com/paper/2105.11320/) (2021)
- [BlitzNet: A Real-Time Deep Network for Scene Understanding](https://mlsanity.com/paper/1708.02813/) (2017)
- [Efficient Continuous-Time SLAM for 3D Lidar-Based Online Mapping](https://mlsanity.com/paper/1810.06802/) (2018)
- [MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views](https://mlsanity.com/paper/2006.05518/) (2020)
- [LiTAMIN2: Ultra Light LiDAR-based SLAM using Geometric Approximation applied with KL-Divergence](https://mlsanity.com/paper/2103.00784/) (2021)
- [Vision System and Depth Processing for DRC-HUBO+](https://mlsanity.com/paper/1509.06114/) (2015)

## Built on by (most cited first, 2 of 2)

- [HDPV-SLAM: Hybrid Depth-augmented Panoramic Visual SLAM for Mobile Mapping System with Tilted LiDAR and Panoramic Visual Camera](https://mlsanity.com/paper/2301.11823/) (2023)
- [Digital Twins and Civil Engineering Phases: Reorienting Adoption Strategies](https://mlsanity.com/paper/2403.02426/) (2024)

## Abstract (arXiv)

The evolution of mobile mapping systems (MMSs) has gained more attention in the past few decades. MMSs have been widely used to provide valuable assets in different applications. This has been facilitated by the wide availability of low-cost sensors, the advances in computational resources, the maturity of the mapping algorithms, and the need for accurate and on-demand geographic information system (GIS) data and digital maps. Many MMSs combine hybrid sensors to provide a more informative, robust, and stable solution by complementing each other. In this paper, we present a comprehensive review of the modern MMSs by focusing on 1) the types of sensors and platforms, where we discuss their capabilities, limitations, and also provide a comprehensive overview of recent MMS technologies available in the market, 2) highlighting the general workflow to process any MMS data, 3) identifying the different use cases of mobile mapping technology by reviewing some of the common applications, and 4) presenting a discussion on the benefits, challenges, and share our views on the potential research directions.