Special Issue "Mobile Robot Olfaction for Real-World Applications–From Disaster Response to Environmental Monitoring"
Deadline for manuscript submissions: closed (10 December 2018)
Prof. Dr. Achim J. Lilienthal
Computer Science, AASS Mobile Robotics and Olfaction Lab, Örebro University, Sweden
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Interests: mobile robotics and robot perception (robot navigation, rich 3D perception, robot map learning, and mobile robot olfaction); human–robot interactions in semi-controlled environments; eye-tracking as a tool for mathematics education
Mobile Robot Olfaction, the research of combining intelligent mobile robots with an artificial sense of smell, has made tremendous progress in the last decade. Important developments in sensor and robot technology, as well as intelligent data processing (fueled by the promising progress in AI/Machine Learning) present the prospect of a wide variety of practical applications. In such applications, gas sensors may be used as one modality on a single robot, a robot team, or as a mobile (robotic) node in a heterogeneous sensor network. On one end of the spectrum are applications in immediate disaster response, where a high degree of mobility, fast operation, and highly-efficient collaboration with human operators and decision makers is crucial and only ad hoc sensor networks are available, if at all. On the other end of the spectrum are long-term environmental monitoring campaigns where response times are often less critical and stationary sensor networks and other permanent infrastructure may exist.
This Special Issue focuses on contributions towards real-world applications of “Mobile Robot Olfaction”. Papers should address how robotic systems, perceptual algorithms, chemical sensors, or approaches to sensor fusion, decision support, human-robot interaction or adaptive sensor planning deal with real-world conditions, e.g., with limited control of the environment, open sampling processes, continuous measurements, rapidly fluctuating concentration levels, turbulent gas dispersal, etc. Papers including prototype demonstrations in relevant real-world scenarios are particularly welcome.
Prof. Dr. Achim J. Lilienthal
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.
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 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.
- Mobile Robot Olfaction
- Chemical sensors
- Electronic Nose or e-nose
- Open sampling system
- Gas sensing
- In situ gas sensing
- Remote gas sensing
- Sensor networks
- Gas dispersal
- Gas detection
- Gas discrimination
- Gas distribution mapping
- Gas source localization
- Robot exploration
- Sensor planning
- Artificial Intelligence
- Machine Learning