On the role and opportunities in teamwork design for advanced multi-robot search systems

Roee M. Francos, Alfred M. Bruckstein

Abstract:

Intelligent robotic systems are becoming ever more present in our lives across
a multitude of domains such as industry, transportation, agriculture, security,
healthcare and even education. Such systems enable humans to focus on the
interesting and sophisticated tasks while robots accomplish tasks that are either
too tedious, routine or potentially dangerous for humans to do. Recent advances
in perception technologies and accompanying hardware, mainly attributed to
rapid advancements in the deep-learning ecosystem, enable the deployment of
robotic systems equipped with onboard sensors as well as the computational
power to perform autonomous reasoning and decision making online. While
there has been significant progress in expanding the capabilities of single and
multi-robot systems during the last decades across a multitude of domains and
applications, there are still many promising areas for research that can advance
the state of cooperative searching systems that employ multiple robots. In this
article, several prospective avenues of research in teamwork cooperation with
considerable potential for advancement of multi-robot search systems will be
visited and discussed. In previous works we have shown that multi-agent search
tasks can greatly benefit from intelligent cooperation between team members
and can achieve performance close to the theoretical optimum. The techniques
applied can be used in a variety of domains including planning against adversarial
opponents, control of forest fires and coordinating search-and-rescue missions.
The state-of-the-art on methods of multi-robot search across several selected
domains of application is explained, highlighting the pros and cons of each
method, providing an up-to-date view on the current state of the domains and
their future challenges.