Navigate-and-Seek: a Robotics Framework for People Localization in Agricultural Environments

Polvara, Riccardo, Del Duchetto, Francesco, Neumann, Gerhard and Hanheide, Marc (2021) Navigate-and-Seek: a Robotics Framework for People Localization in Agricultural Environments. IEEE Robotics and Automation Letters . p. 1. ISSN 2377-3766

Full content URL: https://doi.org/10.1109/LRA.2021.3094557

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Navigate-and-Seek: a Robotics Framework for People Localization in Agricultural Environments
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Abstract

The agricultural domain offers a working environment where many human laborers are nowadays employed to maintain or harvest crops, with huge potential for productivity gains through the introduction of robotic automation. Detecting and localizing humans reliably and accurately in such an environment, however, is a prerequisite to many services offered by fleets of mobile robots collaborating with human workers. Consequently, in this paper, we expand on the concept of a topological particle filter (TPF) to accurately and individually localize and track workers in a farm environment, integrating information from heterogeneous sensors and combining local active sensing (exploiting a robot’s onboard sensing employing a Next-Best-Sense planning approach) and global localization (using affordable IoT GNSS devices). We validate the proposed approach in topologies created for the deployment of robotics fleets to support fruit pickers in a real farm environment. By combining multi-sensor observations on the topological level complemented by active perception through the NBS approach, we show that we can improve the accuracy of picker localization in comparison to prior work.

Keywords:Reactive and Sensor-based Planning, Agriculture robotics, localization, Sensor-fusion, Next-Best-View
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
H Engineering > H671 Robotics
Divisions:College of Science > School of Computer Science
ID Code:45627
Deposited On:08 Jul 2021 13:56

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