Editorial: For the JFR special issue on "Multiple collaborative field robots"

The deployment of multiple robots can lead to important operational benefits in many field applications, for either exploration, surveillance, and intervention missions. With respect to a single robot, teams of robot are obviously less prone to failures, able to simultaneously operate over larger areas, and to convey more and larger variety of payloads. But deploying multiple robots also yields benefits to the robots themselves: the robotics literature has already proposed numerous multirobot schemes in which robots not only cooperate to achieve a given mission, but assist each other to palliate encountered difficulties. Robots can act as communication relays, locate others or merge maps to improve the spatial consistency of maps, carry smaller robots, evolve in formation to ensure safer or quicker motions, and so on. Several contributions of multiple field robot systems have been proposed in a former special issue of the Journal of Field Robotics in 2007.1 Research on such systems has much evolved since, and in 2010, an ambitious challenge has been setup in Adelaide, Australia, in which several teams competed to achieve a surveillance mission with more than a dozen of robots. Six articles of this special issue report on this Multi-Autonomous Ground-robotic International Challenge (MAGIC) sponsored by the The Defence Science & Technology Organization (DSTO) in Australia and the Research Development & Engineering Command (RDECOM) in the United States of America. The MAGIC 2010 contributions highlight the technical challenges in planning, perception, and command and control that have been overcome to operate successfully in the field. In contrast, the last two contributions of this special issue report on field experiments conducted with a team of field robots in environments that were directly and indirectly affected by the 2011 Tohoku earthquake in Sendai, Japan. To lay the foundation for the MAGIC 2010 competition, Finn et al. depict the metrics defined to assess the performance of the MAGIC competitors. After a summary of the scenarios and missions in which numerous heterogeneous robots have to detect and “neutralize” static and mobile targets in a large-scale urban environment, the article depicts the various criteria used to measure the performance of the