Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving
VeDeCoM Institute · Institut national de recherche en sciences et technologies du numérique · +3 more institutions
Abstract
In this paper, we propose a survey of the Simultaneous Localization And Mapping (SLAM) field when considering the recent evolution of autonomous driving. The growing interest regarding self-driving cars has given new directions to localization and mapping techniques. In this survey, we give an overview of the different branches of SLAM before going into the details of specific trends that are of interest when considered with autonomous applications in mind. We first present the limits of classical approaches for autonomous driving and discuss the criteria that are essential for this kind of application. We then review the methods where the identified challenges are tackled. We mostly focus on approaches…
Citation impact
- FWCI
- 727.10
- Percentile
- 100%
- References
- 318
Authors
4- GBGuillaume BressonCorresponding
VeDeCoM Institute
- ZAZayed Alsayed
Institut national de recherche en sciences et technologies du numérique, VeDeCoM Institute
- LYLi Yu
VeDeCoM Institute, Hôpital Saint-Michel, Centre de Robotique, École Nationale Supérieure des Mines de Paris
- SGSébastien Glaser
VeDeCoM Institute
Topics & keywords
- Field (mathematics)
- Simultaneous localization and mapping
- Computer science
- Domain (mathematical analysis)
- Reuse
- Scale (ratio)
- Focus (optics)
- Data science
- Sustainable cities and communities