Precise Positioning and Heading for Autonomous Scouting Robots in a Harsh Environment

Obregón, David; Arnau, Raúl; Campo-Cossio, María; Arroyo-Parras, Juan G.; Pattinson, Michael; Tiwari, Saurabh; Lluvia, Iker; Rey, Oscar; Verschoore, Jeroen; Lenža, Libor; Reyes, Joaquin

doi:10.1007/978-3-030-19651-6_9

Cited by 6 publications

(7 citation statements)

References 16 publications

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“…• It has been verified that the implementation of the relative localization algorithms is correct and its behaviour in simulation environment (with real data) is as expected: smooth solution, no unexpected jumps, able to cope with errors and uncertainty in sensors, etc. • In terms of repeatability and accuracy, the results of the open-sky test are coherent with the conclusions for the test in the greenhouse environment [9]. This was expected since the input of the relative localization is the robot absolute position and heading estimation (which is quite good in both cases) and relative sensor information (which is not affected for the change of environment).…”

Section: Discussionsupporting

confidence: 74%

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Approach for Autonomous Robot Navigation in Greenhouse Environment for Integrated Pest Management

Tiwari

Zheng

Pattinson

et al. 2020

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)

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The use of autonomous robots for certain tasks within agriculture applications can bring many advantages. The H2020-funded GreenPatrol project has developed an autonomous system for pest detection and treatment within commercial greenhouses. In this system the robot will navigate autonomously and regularly inspect crops using an array of cameras and algorithms to detect and treat pests at an early stage in order to improve yield, reduce pesticide use and improve worker conditions. A key enabler for this application is the localization and navigation function of the robot platform. In order to operate independently and autonomously, the robot must know in real-time its precise location and direction of pointing, it must be able to plan a route through the greenhouse from its current location to where it needs to go, it must be able to control its movements to reach its required destination, and it must be able to identify and avoid obstacles that may obstruct its route. In order to achieve these goals the robot subsystems include an absolute localization function, to provide precise absolute position and heading in a global reference frame in real-time, a relative localization function, to provide more fidelity of the exact location and orientation of the robot with respect to its surroundings in the greenhouse, and a navigation function, to plan the route through the greenhouse and provide movement instructions to the robot platform. This paper describes the localization system of the GreenPatrol robot and presents results of testing for each of the functions. The tests include simulations as well as data collections and tests of the real-time system using the robot platform. The results show the high performance of the positioning capability and heading information for the individual systems.

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Section: Discussionsupporting

confidence: 74%

“…The relative localization algorithm relies on ROS [8] software for its implementation in the robot platform (for a detailed description see [9]. It uses the Gmapping algorithm (based on FastSLAM [10] for mapping and AMCL [ [11][12][13][14] for localisation.…”

Section: B Relative Localizationmentioning

confidence: 99%

Approach for Autonomous Robot Navigation in Greenhouse Environment for Integrated Pest Management

Tiwari

Zheng

Pattinson

et al. 2020

2020 IEEE/ION Position, Location and Navigation Symposium (PLANS)

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“…Another industrial use of robotics that have achieved some importance in recent years is agriculture. In [108] the design and verification of the Greenpatrol localization subsystem is described. Greenpatrol is an autonomous robot system intended to operate in light indoor environments, such as greenhouses, detecting and treating pests in high-value crops such as tomato and pepper.…”

Section: Industrial Roboticsmentioning

confidence: 99%

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

et al. 2020

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Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in

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“…This work presents, similarly to [31], a decoupled mobile manipulation control for greenhouse related tasks using the ROS de-facto algorithms [27] and [28]. The navigation is based on latest robotic solutions which have proven to successfully use Galileo Satellites combined with IMU, odometry and range laser sensors for localization [8]. The control architecture follows the hybrid paradigm presented in [40], where rational and efficient deliberative decisions represented by an IPM strategy are combined with reactive behaviors represented by the different navigation, manipulation and vision modules.…”

Section: Related Workmentioning

confidence: 99%

“…Nowadays, robotic solutions combined with computer vision can be used to automate this repetitive inspection task, increasing the reliability, maximizing the health of crops and optimizing the use of pesticides to as little as 5%-10% [6]. For that purpose, robots need to implement plenty of different tasks such as localize themselves [7] and navigate inside greenhouses [8]- [9]; acquire quality pictures to identify pests and their locations [10]; or process the obtained results to generate efficient highlevel instructions to command the robot according to an Integrated Pest Management (IPM) system [11]. However, most research works focus on individual problems neglecting its integration within a single complete solution.…”

Section: Introductionmentioning

confidence: 99%

A Generic ROS-Based Control Architecture for Pest Inspection and Treatment in Greenhouses Using a Mobile Manipulator

et al. 2021

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To meet the demands of a rising population greenhouses must face the challenge of producing more in a more efficient and sustainable way. Innovative mobile robotic solutions with flexible navigation and manipulation strategies can help monitor the field in real-time. Guided by Integrated Pest Management strategies, robots can perform early pest detection and selective treatment tasks autonomously. However, combining the different robotic skills is an error prone work that requires experience in many robotic fields, usually deriving on ad-hoc solutions that are not reusable in other contexts. This work presents Robotframework, a generic ROS-based architecture which can easily integrate different navigation, manipulation, perception, and high-decision modules leading to a faster and simplified development of new robotic applications. The architecture includes generic real-time data collection tools, diagnosis and error handling modules, and user-friendly interfaces. To demonstrate the benefits of combining and easily integrating different robotic skills using the architecture, two flexible manipulation strategies have been developed to enhance the pest detection in its early state and to perform targeted spraying in simulated and field commercial greenhouses. Besides, an additional use-case has been included to demonstrate the applicability of the architecture in other industrial contexts.INDEX TERMS Precision agriculture, robotic control architecture, mobile manipulator, pest detection and treatment, greenhouse.

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Precise Positioning and Heading for Autonomous Scouting Robots in a Harsh Environment

Cited by 6 publications

References 16 publications

Approach for Autonomous Robot Navigation in Greenhouse Environment for Integrated Pest Management

Approach for Autonomous Robot Navigation in Greenhouse Environment for Integrated Pest Management

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

A Generic ROS-Based Control Architecture for Pest Inspection and Treatment in Greenhouses Using a Mobile Manipulator

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