3D sensor planning framework for leaf probing

Conference Article


IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)





Doc link


Download the digital copy of the doc pdf document


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.


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.