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Abstract:
This talk will give an overview of some theoretical and experimental results in the multi-robot field, with a special regard to the multi-UAV case.
It is commonly acknowledged that the major strengths of a multi-robot system are both the resilience to single point failures and the possibility of parallelizing the execution of a given task. These properties can be fully exploited in coverage-like tasks, e.g., exploration, pursuit-evasion (a.k.a. "clearing"), and periodical monitoring (a.k.a. "patrolling"). These tasks, in turn, contain several control and estimation subproblems.
In fact, a coverage-like task often requires to keep a certain optimal arrangement which can be achieved by using an appropriate formation controller. Among the major challenges in this case there are both the decentralization of the controller and the use of cheap and lightweight sensors, like cameras.
Moreover in order to allow a proper fusion of the information gained by every single robot, it is fundamental to share a common reference frame, i.e., to continuously perform a mutual localization among the robots.
A particularly challenging situation in this case is when the robot-detector, which is used for estimating the mutual pose, is anonymous, i.e., it does not retrieve the identity of the detected robot. This represents a usual situation in realistic scenarios when many robots are involved and cameras are used as exteroceptive sensors.
Furthermore, whenever some collaborative task is performed, e.g., formation control or navigation in cluttered environment, it is also of chief importance to keep the connectivity of the group while still allowing for a flexible behavior of the robots, i.e., a time-varying topology.
Finally, the presence of one or more human co-operators may be extremely useful for the multi-robot system, especially whenever the task becomes particularly challenging and requires complex, cognitive capabilities, e.g., in search and rescue operation. A relevant problem in this shared control case is how to balance the robot autonomy with the human assistance.
It has also been proven that the presence of a bilateral (haptic) connection between the human and the machine increases the human situational awareness and improves the quality of the human-robot cooperation. On the other hand, the presence of a force feedback makes the control of the whole system more challenging, e.g., in case long-distances between the co-operator and the robotic group.
