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Modeling, Control, and Haptic Steering of Multi-robot Formations


Franchi,  A
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Franchi, A. (2012). Modeling, Control, and Haptic Steering of Multi-robot Formations. Talk presented at ICRA 2012 - Workshop on Haptic Teleoperation of Mobile Robots: Theory, Applications and Perspectives. St. Paul, MN, USA.

This talk will overview some theoretical and experimental results in the modeling, control and haptic steering of multi-robot formations, 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 subproblems. All these tasks 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. In addition to that, the presence of one or more human co-operators may result 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 operations. 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.