For those among you who are still suffering from travel restrictions in September, we offer a virtual participation option. At a significantly reduced fee, you
• have immediate web access to the MFI papers when the conference starts
• can upload your presentation as a video that will be stored for at least 12 months on the conference website
• can participate in online chats with physical and other virtual participants

Currently, we are preparing for a hybrid meeting with online and on-site participants. However, on-site attendance may be canceled if government regulations disallow the meeting or not enough on-site participants register to break even. A poll to gauge the interest in on-site participation will start in the coming weeks.

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The 2020 IEEE International Conference on Multisensor Fusion and Integration (MFI 2020) is an international conference sponsored by the IEEE Robotics and Automation Society (RAS) and the IEEE Industrial Electronics Society (IES).

September 14 – 16, 2020 (Monday to Wednesday).

First day (Sept. 14) will be tutorials. Second and third day (Sept. 15 & 16) is the regular conference. Welcome reception is in the evening of the first day, Sept. 14. Banquet is on the evening of the second day, Sept. 15.

Authors of high-quality submissions with good ratings will be invited to submit extended versions of their papers to a special issue of the MDPI Journal Sensors.

 

The week after MFI, there is the Radar 2020 Conference in Florence. Use this opportunity to visit two great conferences and see more of Europe.

Karlsruhe is a good place for sightseeing and for enjoying the beautiful scene, castle, and surroundings. The conference is held in the centrally-located IHK Haus der Wirtschaft, from which the castle, museums, and shopping districts are easily accessible. Located in the south-west of Germany, Karlsruhe is also a perfect starting point to visit not only Germany but also France and Switzerland.

Taking Multi-Sensor Fusion to the Next Level: From Theory to Applications

Theory:
Probability theory, Bayesian inference, nonlinear estimation, Dempster-Shafer, fuzzy sets, logic, machine learning, neural networks, distributed architectures
Sensors:
RGB cameras, depth cameras, radar and sonar devices, laser scanner, infrared sensors, IMU, gyroscopes
Algorithms for:
Tracking and localization, SLAM, perception, AI in robotics, cognitive systems, sensor registration, big data, sensor management, distributed sensor systems, recognition, visual servoing, learning by demonstration
Applications:
Sensor networks, multi-robot systems, distributed and cloud robotics, bio-inspired systems, service robots, automation, biomedical applications, autonomous vehicles (land, sea, air), manipulation planning and control, multifinger hands, micro/nano systems, surveillance, multimodal interface and human robot interaction, navigation, Internet-of-Things, smart cities, cyber-physical systems, Industry 4.0, search/rescue/audition, field robotics, swarm robotics, force and tactile sensing, surgical robotics, humanoids, soft-bodied robots