Cooperative control of several robots is currently a very active research area: robotic teams and large-scale swarms are being considered for a broad class of applications, ranging from environmental monitoring, to search and rescue operations, and national security.
Biology provides clear evidence that large-scale groups of animals
coordinate their motion in order to efficiently pursue a collective
objective. The collective behavior arises from local interactions,
driven by individual goals, and with limited information exchange.
The emergence of complex global behavior from simple local rules is by itself fascinating, and has generated a large body of literature in biology, physics, mathematics, and computer science.
Modern technological advances make the deployment of large groups of autonomous mobile agents with on-board computing and communication capabilities increasingly feasible and attractive. As a consequence, the interest of the control community for motion coordination has increased rapidly in the last few years. In this course, we will review the current state of the art in the analysis and design of motion coordination algorithms, for a variety of tasks and application areas, including aircraft/spacecraft formation flying, cooperative control of UAVs, mobile sensor networks, and air traffic control.
• Models of distributed robotic systems; communication and control laws.
• Complexity and performance notions.
• Distributed consensus
• Flocking/Swarming/Formation flight
• Cyclic pursuit and path coverage
• Vehicle routing
• Collision avoidance
• Mixed-Initiative Systems