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This paper presents a vision-based architecture for mobile robot detection and tracking from single frames using off-the-shelf mobile cameras and fiducial markers. A dual unscented Kalman filter is developed to estimate relative position, bearing, heading angles, and leader's velocities. The final goal of this framework is to support the design of robust vision-based algorithms to solve multi-robot...
Recent advances in communication, computation, and embedded technologies support the development of cooperative multivehicle systems. For the purposes of this article, we adopt the following definition of cooperative behavior: "Given some task specified by a designer, a multiple-robot system displays cooperative behavior if, due to some underlying mechanism, for instance, the 'mechanism of cooperation,'...
This paper presents vision-based strategies for decentralized stabilization of unmanned vehicle (UV) formations. The key point of the algorithms is that they only require knowledge of leader-follower relative distances or bearing angles. These data are computed using measurements from pan-controlled off-the-shelf cameras on-board following robots, eliminating sensitivity to information flow among...
This paper presents a vision-based control strategy for decentralized stabilization of unmanned vehicle (UV) formations. The key point of the algorithm is that it only requires knowledge of the leader-follower relative distance and bearing. The approach is based on an output feedback controller that uses a high-gain observer to estimate derivatives of UVs relative positions. Both data are measured...
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