We consider an agricultural automation scenario where a robot, equipped with a camera mounted on a manipulator, is charged with counting the number of apples in an orchard. We focus on the subtask of planning views so as to accurately estimate the number of apples in an apple cluster. We present a method to efficiently enumerate combinatorially distinct world models and to compute the most likely model from one or more views. These are incorporated into single and multi-step planners. We evaluate these planners in simulation as well as with experiments on a real robot.
|Original language||English (US)|
|Title of host publication||IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Dec 13 2017|
|Event||2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017 - Vancouver, Canada|
Duration: Sep 24 2017 → Sep 28 2017
|Name||IEEE International Conference on Intelligent Robots and Systems|
|Other||2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017|
|Period||9/24/17 → 9/28/17|
Bibliographical noteFunding Information:
The authors thank Professors Emily Hoover, Cindy Tong and James Luby from Department of Horticultural Science, University of Minnesota, for their expertise and help with the experiments. Special thanks to Nicolai Haeni for help with experimental set up, camera and hand eye calibration.