TY - JOUR
T1 - Usability analysis of scan matching techniques for localization of field machinery in avocado groves
AU - Auat Cheein, Fernando
AU - Torres-Torriti, Miguel
AU - Rosell-Polo, Joan Ramón
N1 - Funding Information:
The authors would like to thank Santander Grant, CONICYT FONDECYT grant 1171431 , CONICYT Basal grant FB0008 , to the University of Lleida and the Federico Santa María Technical University for their support.
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/7
Y1 - 2019/7
N2 - When working in agricultural environments, specially in groves with dense foliage, machinery positioning systems might suffer from loss of GNSS (Global Navigation Satellite System)signal. The latter motivated the development of new localization strategies that use the environment information to localize the machinery and thus fulfil the required agricultural task. In this work, the usability of five well known scan matching algorithms as sole localization systems using a 2D LiDAR (Light Detection and Ranging)scanner is tested in an avocado grove. The aim is to show the pros and cons of such techniques when the machinery faces a real agricultural environment: presence of slippage, absence of GNSS signal, non-flat terrains in a non-experimental grove and noisy LiDAR readings. The analysis presented herein concludes with a localization error evaluation when the machinery has to travel through a rough avocado alley, showing that amongst all the techniques implemented, the Probabilistic Iterative Correspondence (PIC)and the Sum of Gaussian Scan Correlation (SGSC)presented the lowest localization estimation error and remained consistent from a localization point of view.
AB - When working in agricultural environments, specially in groves with dense foliage, machinery positioning systems might suffer from loss of GNSS (Global Navigation Satellite System)signal. The latter motivated the development of new localization strategies that use the environment information to localize the machinery and thus fulfil the required agricultural task. In this work, the usability of five well known scan matching algorithms as sole localization systems using a 2D LiDAR (Light Detection and Ranging)scanner is tested in an avocado grove. The aim is to show the pros and cons of such techniques when the machinery faces a real agricultural environment: presence of slippage, absence of GNSS signal, non-flat terrains in a non-experimental grove and noisy LiDAR readings. The analysis presented herein concludes with a localization error evaluation when the machinery has to travel through a rough avocado alley, showing that amongst all the techniques implemented, the Probabilistic Iterative Correspondence (PIC)and the Sum of Gaussian Scan Correlation (SGSC)presented the lowest localization estimation error and remained consistent from a localization point of view.
KW - Agricultural robot
KW - LiDAR
KW - Localization
KW - Scan matching
UR - http://www.scopus.com/inward/record.url?scp=85066108813&partnerID=8YFLogxK
U2 - 10.1016/j.compag.2019.05.024
DO - 10.1016/j.compag.2019.05.024
M3 - Article
AN - SCOPUS:85066108813
SN - 0168-1699
VL - 162
SP - 941
EP - 950
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
ER -