Publication
3D sensor planning framework for leaf probing
Conference Article
Conference
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Edition
2015
Pages
6501-6506
Doc link
http://dx.doi.org/10.1109/IROS.2015.7354306
File
Authors
Projects associated
Abstract
Modern plant phenotyping requires active sensing technologies and particular exploration strategies. This article proposes a new method for actively exploring a 3D region of space with the aim of localizing special areas of interest for manipulation tasks over plants. In our method, exploration is guided by a multi-layer occupancy grid map. This map, together with a multiple-view estimator and a maximum-information-gain gathering approach, incrementally provides a better understanding of the scene until a task termination criterion is reached. This approach is designed to be applicable for any task entailing 3D object exploration where some previous knowledge of its general shape is available. Its suitability is demonstrated here for an eye-in-hand arm configuration in a leaf probing application.
Categories
intelligent robots, manipulators, planning (artificial intelligence), robot vision, robots, service robots, uncertainty handling.
Author keywords
next-best-view, planning, information gain, task-based reasoning
Scientific reference
S. Foix, G. Alenyà and C. Torras. 3D sensor planning framework for leaf probing, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015, Hamburg, Germany, pp. 6501-6506.
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