Publication
Task-driven active sensing framework applied to leaf probing
Journal Article (2018)
Journal
Computers and Electronics in Agriculture
Pages
166-175
Volume
147
Doc link
https://doi.org/10.1016/j.compag.2018.01.020
File
Abstract
This article presents a new method for actively exploring a 3D workspace with the aim of localizing relevant regions for a given task. Our method encodes the exploration route in a multi-layer occupancy grid map. This map, together with a multiple-view estimator and a maximum-information-gain gathering approach, incrementally provide a better understanding of the scene until reaching the task termination criterion. This approach is designed to be applicable to any task entailing 3D object exploration where some previous knowledge of its approximate shape is available. Its suitability is demonstrated here for a leaf probing task using an eye-in-hand arm configuration in the context of a phenotyping application (leaf probing).
Categories
manipulators, planning (artificial intelligence).
Scientific reference
S. Foix, G. Alenyà and C. Torras. Task-driven active sensing framework applied to leaf probing. Computers and Electronics in Agriculture, 147: 166-175, 2018.
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