Adaptive heterogeneous multi-robot collaboration from formal task specifications

Philipp Schillinger, Sergio García, Alexandros Makris, Konstantinos Roditakis, Michalis Logothetis, Konstantinos Alevizos, Wei Ren, Pouria Tajvar, Patrizio Pelliccione, Antonis Argyros, Kostas J. Kyriakopoulos, Dimos V. Dimarogonas

Research output: Contribution to journalArticlepeer-review


Efficiently coordinating different types of robots is an important enabler for many commercial and industrial automation tasks. Here, we present a distributed framework that enables a team of heterogeneous robots to dynamically generate actions from a common, user-defined goal specification. In particular, we discuss the integration of various robotic capabilities into a common task allocation and planning formalism, as well as the specification of expressive, temporally-extended goals by non-expert users. Models for task allocation and execution both consider non-deterministic outcomes of actions and thus, are suitable for a wide range of real-world tasks including formally specified reactions to online observations. One main focus of our paper is to evaluate the framework and its integration of software modules through a number of experiments. These experiments comprise industry-inspired scenarios as motivated by future real-world applications. Finally, we discuss the results and learnings for motivating practically relevant, future research questions.

Original languageEnglish (US)
Article number103866
JournalRobotics and Autonomous Systems
StatePublished - Nov 2021


  • Abstraction
  • HRI
  • Heterogeneous robots
  • Multi-robot
  • Robotics
  • Task allocation
  • Task decomposition
  • Temporal logic

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Computer Science Applications
  • General Mathematics


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