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This article describes a simple monocular navigation system for a mobile robot based on the map-and-replay technique. The presented method is robust, easy to implement, does not require sensor calibration or structured environment and its computational complexity is independent of the environment size. The method can navigate a robot while sensing only one landmark at a time, making it more robust than other monocular approaches. The aforementioned properties of the method allow even low-cost robots to effectively act in large outdoor and indoor environments with natural landmarks only.The basic idea is to utilize a monocular vision to correct only the robot's heading and leaving distance measurements just to the odometry. The heading correction itself can suppress the odometric error and prevent the overall position error from diverging.The influence of a map-based heading estimation and odometric errors on the overall position uncertainty is examined. A claim that for closed polygonal trajectories the position error of this type of navigation does not diverge is stated. The claim is defended mathematically and experimentally. The method has been experimentally tested in a set of indoor and outdoor experiments, during which the average position errors have been lower than 0.3 m for paths over 1 km long.

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The final publication is available at http://ijr.sagepub.com/content/33/10/1393 Copyright noticeThe copyright to the Contribution identified above is transferred to SAGE Publications. The copyright transfer covers the sole right to print, publish, distribute and sell throughout the world the said Contribution and parts thereof, including all revisions or versions and future editions thereof and in any medium, such as in its electronic form (offline, online), as well as to translate, print, publish, distribute and sell the Contribution in any foreign languages and throughout the world.Coordination and navigation of heterogeneous MAV-UGV formations localized by a "hawk-eye" like approach under a model predictive control scheme AbstractAn approach for coordination and control of 3D heterogeneous formations of unmanned aerial and ground vehicles under hawk-eye like relative localization is presented in this paper. The core of the method lies in the use of visual top-view feedback from flying robots for the stabilization of the entire group in a leader-follower formation. We formulate a novel Model Predictive Control (MPC) based methodology for guiding the formation. The method is employed to solve the trajectory planning and control of a virtual leader into a desired target region. In addition, the method is used for keeping the following vehicles in the desired shape of the group. The approach is designed to ensure direct visibility between aerial and ground vehicles, which is crucial for the formation stabilization using the hawk-eye like approach. The presented system is verified in numerous experiments inspired by search and rescue applications, where the formation acts as a searching phalanx. In addition, stability and convergence analyses are provided to explicitly determine the limitations of the method in real-world applications.

An algorithm for autonomous deployment of groups of Micro Aerial Vehicles (MAVs) in the cooperative surveillance task is presented in this paper. The algorithm enables to find a proper distributions of all MAVs in surveillance locations together with feasible and collision free trajectories from their initial position. The solution of the MAV-group deployment satisfies motion constraints of MAVs, environment constraints (non-fly zones) and constraints imposed by a visual onboard relative localization. The onboard relative localization, which is used for stabilization of the group flying in a compact formation, acts as an enabling technique for utilization of MAVs in situations where an external local system is not available or lacks the sufficient precision.

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