This monograph covers theoretical and practical aspects of the problem of autonomous guiding of unmanned aerial manipulators using visual information. For the estimation of the vehicle state (position, orientation, velocity, and acceleration), the authors propose a method that relies exclusively on the use of low-cost and highrate sensors together with low-complexity algorithms. This is particularly interesting for applications in which on board computation with low computation power is needed. Another relevant topic covered in this monograph is visual servoing. The authors present an uncalibrated visual servo scheme, capable of estimating at run time, the camera focal length from the observation of a tracked target. The monograph also covers several control techniques, which achieve a number of tasks, such as robot and arm positioning, improve stability and enhance robot arm motions. All methods discussed in this monograph are demonstrated in simulation and through real robot experimentation. The text is appropriate for readers interested in state estimation and control of aerial manipulators, and is a reference book for people who work in mobile robotics research in general.
This monograph introduces a unifying framework for mapping, planning and exploration with mobile robots considering uncertainty, linking such problems with a common SLAM approach, adopting Pose SLAM as the basic state estimation machinery. Pose SLAM is the variant of SLAM where only the robot trajectory is estimated and where landmarks are used to produce relative motion measurements between robot poses. With regards to extending the original Pose SLAM formulation, this monograph covers the study of such measurements when they are obtained with stereo cameras, develops the appropriate noise propagation models for such case, extends the Pose SLAM formulation to SE(3), introduces information-theoretic loop closure tests, and presents a technique to compute traversability maps from the 3D volumetric maps obtained with Pose SLAM. A relevant topic covered in this monograph is the introduction of a novel path planning approach that exploits the modeled uncertainties in Pose SLAM to search for the path in the pose graph that allows the robot to navigate to a given goal with the least probability of becoming lost. Another relevant topic is the introduction of an autonomous exploration method that selects the appropriate actions to drive the robot so as to maximize coverage, while minimizing localization and map uncertainties. This monograph is appropriate for readers interested in an information-theoretic unified perspective to the SLAM, path planning and exploration problems, and is a reference book for people who work in mobile robotics research in general.
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