4 October, 2019

SS08 – Special Session on Soft Computing applied to robotics and autonomous vehicles


In the past robotics and vehicle design were two separated engineering fields, but providing autonomous capabilities to vehicles has introduced them into the robotics world. In fact, both research areas are nowadays converging to the mobile robotics field. In order to satisfy the growing demands of the industry and society, these mobile robots need to develop perception and learning capabilities to work properly in changing environments. Neural networks, fuzzy logic, evolutionary computation and other Soft Computing techniques can contribute to advance on robotics and autonomous vehicles, as well as to merge both research fields.

The goal of this special session is to provide a platform for researchers, engineers, and industrial practitioners from different fields to share and exchange their ideas, research results, and experiences in the field of soft computing techniques applied to robotics and autonomous vehicles. Contributions to this special session are welcome to present and discuss novel methods, algorithms, frameworks, architectures, platforms, and applications.


Session topics include but are not limited to:

  • Autonomous vehicles applications and methods
  • Modelling and intelligent control of autonomous vehicles (UAV, AGV, USV, …..)
  • Collaborative applications and techniques
  • Robotics applications and techniques
  • Path planning strategies
  • Navigation algorithms
  • Traffic algorithms
  • Fleet management
  • Context awareness technologies

Session Chairs

  • J. Enrique Sierra García, ASTI Mobile Robotics (Spain)
  • Matilde Santos Peñas, Complutense University of Madrid (Spain)
  • Ioannis Mariolis , Centre for Research and Technology Hellas (Greece)
  • Carlos Cambra Baseca, University of Burgos (Spain)


Dr. J. Enrique Sierra

ASTI Mobile Robotics

Autovía A1 km. 213,5 – 09390 Madrigalejo del Monte, Burgos (Spain)

E-mail: enriquesg@asti.es

Additional Information

The session will be technically endorsed by CoLLaboratE project (https://collaborate-project.eu/), which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 820767.