Service Robotics in Challenging Environments


For the last six decades, we have witnessed the gradual robotic colonization of industrial spaces with great success. These spaces are often specially adapted for robots, so that they can perform their tasks as precisely and efficiently as possible. Robotics has slowly started its journey from industrial environments to service environments by developing systems to assist humans, typically by performing jobs that are dirty, dull, distant, dangerous, or repetitive.

Service robotics encompass a broad field of applications, most of which having unique designs. Differently to industrial robots, service applications are commonly developed in rich/complex dynamic scenarios, where the robot must explicitly consider uncertain in both perception and action. To deal with such a variety of environments and applications, service robotics span equally grounded, aerial, and underwater systems.

Thus, many of these service applications requires of GPS-denied localization, motion planning in dynamic or partially unknown environments, limited robot perception, specific computer vision skills, limited communications, or complex decision making, to name a few. Although robot autonomy has advance significantly in the last years, many of the solutions to these requirements in the state of the art lack the robustness and reliability required work in challenging environments. Elements as low visibility, fog, dynamic environments, or partial environment information use to degrade the quality of the solutions.

This special session will focus on the robot technologies (perception, planning, localization, actuation) required to develop autonomous or semi-autonomous tasks in challenging environments out of factories, including but limited to:

• GPS-denied localization

• Control in complex environments (slippery terrains, wind turbulences, ocean currents, etc)

Planning in dynamic scenarios

Reliable inter-robot communications

Perception in low visibility

Mapping or SLAM in low visibility

Reliable/robust multi-sensor estimations


  • Robot perception in low visibility environments

  • Reliable robot localization and SLAM in GPS-denied environment

  • Robot planning in dynamic and partially known environments

  • Robot control in complex scenarios


  • Fernando Caballero, Universidad de Sevila, Spain

  • Pascual Campoy, Universidad Politécnica de Madrid, Spain

Program Committee

  • Luis Merino Cabañas, Universidad Pablo de Olavide, Spain

  • Juan Andrade Cetto, CSIC: Instituto de Robótica e Informática Industrial, Spain

  • Alberto Ortiz Rodriguez, Universidad de las Islas Baleares, Spain

  • Arturo de la Escalera Hueso, Universidad Carlos III de Madrid, Spain

  • José María Armingol Moreno, Universidad Carlos III de Madrid, Spain

  • Danilo Tardioli, Centro Universitario de la Defensa, Spain