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Titlebook: Intelligent Autonomous Systems 15; Proceedings of the 1 Marcus Strand,Rüdiger Dillmann,Stefano Ghidoni Conference proceedings 2019 Springer

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书目名称Intelligent Autonomous Systems 15
副标题Proceedings of the 1
编辑Marcus Strand,Rüdiger Dillmann,Stefano Ghidoni
视频videohttp://file.papertrans.cn/470/469378/469378.mp4
概述Presents the latest research on and innovations in intelligent autonomous systems.Addresses the emerging role of autonomous robots in industrial production.Offers a rich source of ideas for new resear
丛书名称Advances in Intelligent Systems and Computing
图书封面Titlebook: Intelligent Autonomous Systems 15; Proceedings of the 1 Marcus Strand,Rüdiger Dillmann,Stefano Ghidoni Conference proceedings 2019 Springer
描述This book presents the latest advances and research achievements in the fields of autonomous robots and intelligent systems, presented at the IAS-15 conference, held in Baden-Baden, Germany, in June 2018. It brings together contributions from researchers, engineers and practitioners from all over the world on the main trends of robotics: navigation, path planning, robot vision, human detection, and robot design – as well as a wide range of applications. This installment of the conference reflects the rise of machine learning and deep learning in the robotics field, as employed in a variety of applications and systems. All contributions were selected using a rigorous peer-review process to ensure their scientific quality. The series of biennial IAS conferences was started in 1986: since then, it has become an essential venue for the robotics community.
出版日期Conference proceedings 2019
关键词Autonomous Systems; Computational Intelligence; Intelligent Systems; Conference proceedings; Intelligent
版次1
doihttps://doi.org/10.1007/978-3-030-01370-7
isbn_softcover978-3-030-01369-1
isbn_ebook978-3-030-01370-7Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Robust Path Planning Against Pose Errors for Mobile Robots in Rough Terrainng on rough terrain cannot follow a planned path perfectly because of uncertainties such as pose errors. In this work, we represent such pose errors as error ellipsoids to use on collision check with obstacles in a map. The error ellipsoids are estimated based on extended Kalman filter (EKF) that in
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Stereo Vision-Based Optimal Path Planning with Stochastic Maps for Mobile Robot Navigationodology of getting 3D point cloud from disparity images, its transformation to 2D stochastic navigation map with occupancy grid cell values assigned from the set {obstacle, unoccupied, occupied}. We re-examined and extended this methodology with a combination of A-Star with binary heap algorithms fo
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Variance Based Trajectory Segmentation in Object-Centric Coordinatesy times, there is a property that the variance of the hand trajectory in object-centric coordinates becomes small at the stage of acting on the object. In this paper, we focused on human demonstration in object-centric coordinates, and proposed a task segmentation method and motion generation of a r
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An Integrated Planning of Exploration, Coverage, and Object Localization for an Efficient Indoor Sem various activities: exploration, (2D or 3D) geometrical mapping, and object detection and localization. An efficient mapping entails selecting good viewpoints. Since a good viewpoint for one activity and that for another could be shared or conflicting, it is desirable to deal with all such activiti
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Unsupervised Hump Detection for Mobile Robots Based On Kinematic Measurements and Deep-Learning Basever, even such small irregularities can have a tremendous effect on the robot’s stability and the path quality. As a basis to develop anomaly detection algorithms, example kinematics data is collected for an overrun of a cable channel and a bulb plate. A recurrent neuronal network (RNN), based on th
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Efficient Coverage of Unstructured Environmentsistic to make the minimum sum of altitudes (MSA) decomposition, which computes an optimal exact cellular decomposition, applicable to more complex environments. Contrary to previous approaches, our technique explicitly takes into account different entry and exit points for the obtained cells and hen
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