Localization Algorithm Design and Evaluation for an Autonomous Pollination Robot

Chizhao Yang, Ryan M. Watson, Jason N. Gross, and Yu Gu

Abstract:	As the population of natural pollinators declines, there is an increased desire to supplement their functionally artificially. To support agriculture productions when natural pollinators are not available, a methodology for realizing artificial pollination that has received considerable interest – both within the academic and commercial communities – is the utilization of autonomous robotic systems. One essential component within the complex architecture of an autonomous pollinating robot is an accurate, efficient, and robust localization and mapping subsystem (i.e., a subsystem that maps the environment and localizes the robot). This paper details the algorithmic design of a factor-graph based localization and mapping subsystem used to operate within a greenhouse environment. The presented system is validated on multiple collected data-sets both in the greenhouse and an outdoor farm.
Published in:	Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019) September 16 - 20, 2019 Hyatt Regency Miami Miami, Florida
Pages:	2702 - 2710
Cite this article:	Yang, Chizhao, Watson, Ryan M., Gross, Jason N., Gu, Yu, "Localization Algorithm Design and Evaluation for an Autonomous Pollination Robot," Proceedings of the 32nd International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2019), Miami, Florida, September 2019, pp. 2702-2710. https://doi.org/10.33012/2019.17099
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