The availability of accurate geospatial information and reliable ubiquitous localization systems are key factors in a number of applications and contexts, ranging from location-based services and smart cities, to the use of terrestrial, underground, aerial and underwater autonomous robots, autonomous driving, and positioning in GNSS-denied environments, just to mention a few. The recent development of effective artificial intelligence tools also plays a core role in these applications, in order to enable an effective machine interpretation and understanding of geospatial data.
The previously mentioned applications are usually related to the use of mobile platforms working in real time: these requirements imply the use of effective mobile mapping systems. Furthermore, the need for ubiquitous accurate localization goes beyond the possibilities of stand-alone GNSS positioning. In this context, simultaneous mapping and localization (SLAM) techniques have proved to be effective solutions in order to properly compensate for the unreliability of GNSS in certain working conditions, while preserving the possibility of fast accurate mapping.
Motivated by the above considerations, this workshop will seek contributions covering advanced topics related to the state of the art and future trends of SLAM approaches for mobile mapping and robot intelligence, focusing both on the mapping and localization problems, and on the artificial intelligence tools needed in order to enable mobile perception and real time machine understanding of geospatial data.


Themes of event:
  • Simultaneous localization and mapping (SLAM) techniques
  • Semantic and metric SLAM
  • Calibration of mobile (multi) sensor systems
  • Evaluation of localization and mapping sensors for indoor and outdoor robotics
  • Learning and optimization for robotics multi-sensor integration
  • New robotic mapping applications
  • Mapping representations for robotics and autonomous vehicle navigation
  • Robotic mapping benchmarks
  • On-board sensors of autonomous systems for mapping and map updating purposes
  • Perception in non-controlled or complex or non-cooperative environments
  • Spatial representations, data structures and database technologies for large scale mapping and map updating
  • Synergies between indoor mobile mapping and building information modelling (BIM)
  • Integration of SLAM with inertial sensors
  • Low cost sensors for mapping and localization

Scientific Committee:
  • Yuan Zhuang, Wuhan University, China
  • Vincenzo di Pietra Politecnico di Torino, Italy
  • Stephan Nebiker, FHNW, Switzerland
  • Heikki Hyyti, NLS, Finnland
  • Phillipp Fanta-Jende, AIT, Austria
  • Norbert Haala, University of Stuttgart