Current challenges in research and development of multi-robot systems


The use of multiple cooperating agents creates a more capable robotic system and allows addressing complex tasks of interest in diverse domains. Multi-robot systems continue to be a rich field of study with important application areas: exploration and monitoring of large environments, cooperative transport of complex objects, or warehouse logistics, among others. Relevant efforts are currently being made towards enhancing the capability of multi-robot systems to (i) operate in highly dynamic conditions or under severe perception and communication limitations, (ii) interact with highly complex objects, or (iii) guarantee robust and resilient performance. The existing challenges can be addressed via model-based solutions, and also through approaches based on machine learning, which bring about exciting prospects for progress in this field. Moreover, due to the prevalence and increasing complexity of multi-robot applications, there is a growing need for suitable software tools to be used at the prototyping and deployment stages. This special session aims to present works contributing to the advancement of the field of multi-robot systems in the described context.


  • Multi-robot task planning and motion planning

  • Multi-robot motion coordination (flocking, coverage, formation control, etc.)

  • Multi-robot perception and estimation

  • Distributed algorithms in robotics

  • Robot networks

  • Robot swarms

  • Heterogeneous multi-robot teams

  • Multi-robot manipulation

  • Software tools for multi-robot systems

  • Machine learning for multi-robot systems


  • Miguel Aranda, Universidad de Zaragoza, Spain

  • Rosario Aragüés, Universidad de Zaragoza, Spain

  • Gonzalo López-Nicolás, Universidad de Zaragoza, Spain

  • María Guinaldo, UNED, Spain

  • Antonio González, Universitat Politècnica de València, Spain