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Saint Petersburg, Russia

Matveev A.,Saint Petersburg University 28 | Semakova A.,Saint Petersburg University 28 | Savkin A.,University of New South Wales
2015 10th Asian Control Conference: Emerging Control Techniques for a Sustainable World, ASCC 2015 | Year: 2015

A planar Dubins-car like robot is controlled by upper limited angular velocity. There is a team of irregularly moving targets in the plane. The robot measures only the relative distances to the targets and cannot distinguish among them. A sliding mode control law is proposed that drives the root mean squared distance to a target to a pre-specified value; the mean is taken over all targets. This law is justified by a non-local convergence result: it is proved that the law ensures perfectly circumnavigating the targets at exactly the required mean distance. The convergence and performance of the control law are confirmed by computer simulations. © 2015 IEEE. Source


Ovchinnikov K.,Saint Petersburg University 28 | Semakova A.,Saint Petersburg University 28 | Matveev A.,Saint Petersburg University 28
Robotics and Autonomous Systems | Year: 2015

Several anonymous Dubins-car like mobile robots travel in a planar environment that hosts a scalar field, like the level of radiation or concentration of a contaminant. The objective is to co-operatively detect and localize the boundary of the set where the field value exceeds a certain threshold. The robots suffer from deficits of competence, communication, perception, and maneuverability: they do not know the field profile a priory, are not aware of the team size, cannot communicate with and recognize one another, can measure only the value of the field at the current location, are subjected to nonholonomic constraints, and are able to move along paths of only limited curvatures. We propose a new decentralized navigation strategy that drives all robots to the desired environmental boundary, with subsequent stable circulation along it. This strategy is based on an autonomous control of every robot, prevents collisions between them and ultimately ensures their pseudo-uniform distribution over the boundary to better utilize the resources of the team for representatively portraying the boundary. Furthermore, the proposed control scheme does not employ gradient estimation, which typically needs ineffective concentration of robots into tight clusters, and is non-demanding with respect to both computation and motion. Its mathematically rigorous justification is provided. The effectiveness of the proposed guidance law is confirmed by computer simulations and real-world experiments. © 2015 Elsevier B.V. All rights reserved. Source

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