Best Practice in Simultaneous Localization and Mapping (SLAM)
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 33386
Special Issue Editors
Interests: SLAM; computer vision; walking robots; robot perception; sensor calibration
Interests: SLAM; localization; mapping; robot perception
Special Issue Information
Dear Colleagues,
The recent years have seen SLAM algorithms being deployed in a variety of different platforms, with increasing levels of accuracy and robustness. The domain of applications is vast and enables legged or wheeled ground vehicles, drones, and underwater robots to accomplish complex tasks such as managing warehouses, autonomous driving, house cleaning, and more. Transitioning from controlled lab environments to in-field deployment is very challenging, and is often made possible via the accumulation of solid expertise on practical aspects related to SLAM, such as time synchronization, transmission delays, sensor acquisition, noise, adverse operating conditions, and model uncertainties. Solutions to these problems are often the result of knowledge and expertise accumulated and consolidated over time within a specific research team. Sharing this technical expertise with the research community in the form of best practices would be highly beneficial, as it is a key enabler to unleash the true potential of robot autonomy.
The developments in SLAM also coincide with further developments in autonomous robots. The availability of ubiquitous localization techniques drives development forward in planning and control domains that when combined form an autonomous agent. In this Special Issue, we are also interested in new developments and challenges faced when dealing with autonomy during real-life applications. More broadly, we also kindly encourage submissions dealing with methods that are critical components for a real-life operation like calibration solutions.
The goal of this Special Issue is to invite high-quality, state-of-the-art research papers that deal with challenging issues in SLAM. We solicit original papers of unpublished and completed research that is not currently under review by any other conference/magazine/journal. Topics of interest include but are not limited to the list below:
- Best practice in visual, LiDAR, and radar SLAM;
- Fault detection and recovery in SLAM;
- Tight integration of SLAM algorithms with planning and control systems;
- Emerging SLAM application domains and their inherent challenges;
- Calibration methods for single and multi-cue SLAM systems;
- SLAM with non-conventional sensors;
- Core SLAM aspects:
- Position tracking;
- Optimization;
- Uncertainty estimation (also marginalization);
- Data association;
- Loop closing;
- Learning-based methods to enhance model-based SLAM systems.
Dr. Michał R. Nowicki
Prof. Giorgio Grisetti
Dr. Marco Camurri
Guest Editors
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