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ROSI: A Robotic System for Harsh Outdoor Industrial Inspection - System Design and Applications

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Abstract

Belt Conveyors are essential for transporting dry bulk material in different industries. Such structures require permanent inspections, traditionally executed by human operators based on cognition. To improve working conditions and process standardization, we propose a novel procedure to inspect conveyor structures with a ground robot composed by a mobile platform, a robotic arm, and a sensor-set. Based on field experience, we introduce ROSI, a new robotic device designed for long-term operations in harsh outdoor environments. The mobile robot has a hybrid locomotion system, using wheels to reduce energy consumption while covering long distances, and also flippers with tracks to improve mobility during obstacle negotiation. A mechanical passive switch allows decoupling tracks’ traction, reducing components wear and energy consumption without raising mechanical complexity. Aiming the robot-assisted operation, control strategies help to (i) command both the mobile platform and a robotic manipulator considering the system whole-body model, (ii) adjust the contact force for touching the conveyor structure during vibration inspection, and (iii) climb stairs while automatically adjusting the flippers. Machine Learning algorithms detect conveyors’ dirt build-ups, roller failures, and bearing faults by processing visual, thermal and sound data as inspection functionalities. The algorithms training and validation use a dataset collected from running conveyors at Vale, presenting detection accuracy superior to 90%. Field test results in a mining site demonstrate the robot capabilities to stand for the harsh operating conditions while executing all the required inspection tasks, stating ROSI as a disruptive solution for Belt Conveyor inspections and other general industrial operations.

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Acknowledgements

This work was financed in part by Brazilian National Research Council CNPq, the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brasil (CAPES) - Finance Code 88887.136349/2017-00 and 001, VALE S.A. and Instituto Tecnologico Vale.

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Authors and Affiliations

  1. Department of Electrical Engineering, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Filipe Rocha, Raphael F. S. Pereira, Henrique D. Faria, Thales H. Silva, Ricardo H. R. Andrade, Evelyn S. Barbosa, Wenderson G. Serrantola, Luiz Moura, Ramon R. Costa & Fernando Lizarralde

  2. Vale S.A., Rio de Janeiro, Brazil

    Gabriel Garcia & André Franca

  3. Instituto Tecnológico Vale, Ouro Preto, Brazil

    André Almeida, Héctor Azpúrua & Gustavo Pessin

  4. Universidade Federal de Ouro Preto, Ouro Preto, Brazil

    Emanuel Cruz & Wagner Andrade

  5. Department of Electrical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil

    Gustavo M. Freitas

Authors
  1. Filipe Rocha
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  2. Gabriel Garcia
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  3. Raphael F. S. Pereira
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  4. Henrique D. Faria
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  7. Evelyn S. Barbosa
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  9. Emanuel Cruz
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  10. Wagner Andrade
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  11. Wenderson G. Serrantola
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  14. André Franca
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  15. Gustavo Pessin
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  16. Gustavo M. Freitas
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  18. Fernando Lizarralde
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Correspondence to Filipe Rocha.

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Rocha, F., Garcia, G., Pereira, R.F.S. et al. ROSI: A Robotic System for Harsh Outdoor Industrial Inspection - System Design and Applications. J Intell Robot Syst 103, 30 (2021). https://doi.org/10.1007/s10846-021-01459-2

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  • DOI: https://doi.org/10.1007/s10846-021-01459-2

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