Special Issue "Vision-Based Sensors in Field Robotics"
Deadline for manuscript submissions: closed (1 October 2016).
Interests: marine robotics; real-time vision; control architectures for autonomous mobile robots
Special Issues and Collections in MDPI journals
Interests: object detection; semantic segmentation; virtual worlds; domain adaptation; transfer learning; autonomous driving
Vision-based sensing is widely used in many robotic and automation applications, including localization, mapping, object recognition, guidance or obstacle avoidance, among others. Nowadays, mobile robots are continuously being adapted to carry out a wider range of applications in progressively more demanding environments. Quite often, vision plays an essential role to make these challenging tasks possible, although it can be fused or reinforced with other sensing modalities.
This Special Issue is aimed at bringing together novel solutions related to sensing and acting in field robotics applications. We focus our interest in manuscripts thoroughly describing new vision-based systems to be used in highly unstructured and dynamic environments as well as innovative and efficient methods to process the data gathered in these scenarios. Both original research articles and reviews are welcome.
Original research papers must not rely on processing information from public datasets, but describe complete solutions to specific field robotics applications, including sensor systems, fundamental methods and experimental results. Manuscripts can alternatively focus on presenting new (annotated) datasets gathered by novel vision-based sensors and used in field robotics applications, thus contributing to future benchmarking.
Reviews, presenting an analytical up-to-date overview of the state-of-the-art, would also be appropriate, provided they incorporate some quantitative and qualitative scoring of the exposed solutions through publicly available data.
Robotic solutions, including, but not limited to, the following field applications, are encouraged:
If you have suggestions that you would like to discuss beforehand, please feel free to contact us. We look forward to your participation in this Special Issue.
Dr. Gabriel Oliver-Codina
Dr. Nuno Gracias
Dr. Antonio M. López
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Unmanned Aerial Vehicles
- Space and Planetary robotics
- Surface and Underwater Autonomous Vehicles
- Defense and Security robotized systems
- Demining and Clearance of Unexploded Ordnance applications
- Image-based localization in unstructured and dynamic scenarios
- Multi-sensor integration
- Off-road autonomous driving
- Search and rescue robots
- Mining and subterranean robots
- Field operational tests of autonomous vehicles