Human Factors issues for Interaction with Bio-Inspired Swarms

Robotic systems composed of a large number of entities, often called robot swarms, are envisioned to play an increasingly important role in applications such as search, rescue, surveillance, and reconnaissance operations. Nowadays, many mobile robots that are deployed for such applications are still tele-operated by a single or multiple operators. While these platforms are individually very capable, the development of cheaper hardware allows the consideration of swarm systems composed of many more robots but with each individual being far less powerful. Examples from biology indicate that such systems can be collectively more powerful than any individual robot within the team and also more than many larger, more sophisticated individual robots. Enabling a human to control such bio-inspired systems is a considerable challenge due to the limitations of each individual robot and the sheer number of robots that need to be coordinated to successfully complete a mission. Autonomous algorithms provide an opportunity to mitigate some of the complexity an operator faces in controlling such swarms, but it is not clear either (a) which tasks will ultimately need to be executed by the operator rather than by the swarm, or (b) what kinds of interactions would be needed