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Gripper Design for Radio Base Station Autonomous Maintenance System

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Abstract

For an autonomous system to perform maintenance tasks in a networking device or a radio base station (RBS), it has to deal with a series of technological challenges ranging from identifying hardware-related problems to manipulating connectors. This paper describes the development of a robot maintenance system dedicated to detect and resolve faulty links caused by unplugged or poorly connected cables. Although the maintenance system relies on four subsystems, we significantly focus on our low-cost and efficient custom gripper solution developed to handle RJ45 Ethernet connectors. To examine our gripper, we conducted three experiments. First, a qualitative questionnaire was submitted to 30 users in the case of the teleoperated scenario of the gripper attached to a robotic arm. Similarly, we also tested the automatic operation mode. The results showed that our system is reliable and delivers a highly efficient maintenance tool in both teleoperated and autonomous operation modes. The practical experiment containing the removal or unplugging of connectors demonstrated our gripper’s ability to adequately handle these, whereas the feedback from the questionnaire pointed to a positive user experience. The automatic test assessed the gripper’s robustness against the continuous operation.

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Acknowledgements

This work was supported by the Research, Development and Innovation Center, Ericsson Telecommunications Inc., Brazil.

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Correspondence to Gabriel Reis, Marrone Dantas, Daniel Bezerra, Gibson Nunes, Pedro Dreyer, Carolina Ledebour, Judith Kelner, Djamel Sadok, Ricardo Souza, Silvia Lins or Maria Marquezini.

Additional information

Recommended by Associate Editor Yuan-Qing Xia

Colored figures are available in the online version at https://link.springer.com/journal/11633

Gabriel Reis received the B. Eng. degree in mechanical engineering from Federal University of Pernambuco (UFPE), Brazil in 2016. Currently, he is a master student at UFPE. He is also a researcher at Research Group of Networks and Telecommunications (GPRT), UFPE, Brazil.

His research interests include robotics, feedback control systems, and control theory.

E-mail: gabriel.souza@gprt.ufpe.br

ORCID iD: 0000-0003-1663-1336

Marrone Dantas received the B. Sc. degree in computer science from Federal Rural University of Pernambuco, Brazil in 2017. and the M. Sc. degree in computer science from Federal University of Pernambuco (UFPE), Brazil in 2019. He is currently a Ph. D. degree candidate and a researcher at Research Group of Networks and Telecommunications (GPRT), UFPE, Brazil.

His research interests include pattern recognition, machine learning, computer vision and image processing.

E-mail: marrone.dantas@gprt.ufpe.br

ORCID iD: 0000-0002-7927-8472

Daniel Bezerra received the B. Eng. degree in computer engineering and the M. Sc. degree in computer science both from Federal University of Pernambuco (UFPE), Brazil in 2015 and 2018, respectively. He is currently a Ph. D. degree candidate at Informatics Center of UFPE, Brazil. He works at Research Group of Networks and Telecommunications (GPRT), UFPE, Brazil.

His research interests include distributed systems, networked robotics, and Internet of Things (IoT).

E-mail: daniel.bezerra@gprt.ufpe.br

ORCID iD: 0000-0002-3839-3642

Gibson Nunes received the M. Sc. degree in computer science from the UFPE, Brazil in 2017. He is currently a Ph. D. degree candidate at Informatics Center, UFPE, Brazil. He is a researcher at Research Group of Networks and Telecommunications (GPRT), UFPE, Brazil.

His research interests include computational intelligence, clustering analysis, data mining, prototyping of printed circuit boards, field programmable gate array (FPGA), testing and verification of register transfer level (RTL) systems.

E-mail: gibson.nunes@gprt.ufpe.br

ORCID iD: 0000-0001-9023-4019

Pedro Dreyer received the B. Eng. degree in mechanical engineering at Federal University of Pernambuco (UFPE), Brazil in 2017, and received the M. Sc. degree in computer science from UFPE, Brazil in 2019. He is currently working in the areas of robotics and computer vision at Research Group of Networks and Telecommunications (GPRT), UFPE, Brazil.

His research interests include machine learning and computer simulations.

E-mail: pedro.dreyer@gprt.ufpe.br

Carolina Ledebour received the B. A. degree in design from Federal University of Pernambuco (UFPE), Brazil in 2010, received the M. Sc. degree in computer science also from UFPE, Brazil in 2017. She is currently a Ph. D. degree candidate at UFPE, Brazil.

Her research interests include humanrobot interaction, human-robot collaboration, smart environments interaction, and IoT.

E-mail: carolina.cani@gprt.ufpe.br

Judith Kelner received the Ph. D. degree from Computing Laboratory, University of Kent at Canterbury, UK in 1993. She is a full professor at Federal University of Pernambuco, Brazil since 1979. Currently, she leads the Virtual Reality and Multimedia Research Group (GRVM) team as well as coordinates a number of research projects in Brazil.

Her research interests include multimedia systems, design of virtual and augmented reality applications, and smart communication devices.

E-mail: jk@gprt.ufpe.br

Djamel Sadok received the Ph.D. degree in computer science from University of Kent, UK in 1990. Next, he was a research fellow at University College London working on OSI security. He leads the Research Group of Networks and Telecommunications (GPRT), UFPE, Brazil in the area of computer communications cooperating with Research Department of Ericsson, He is full professor and a senior IEEE member since 1993.

His research interests include cloud and 5G availability, industry 4.0 and the study of human robot risk management, and energy management.

E-mail: jamel@gprt.ufpe.br

Ricardo Souza received the B. Eng. degree in electrical engineering from Federal University of Campina, Brazil in 2007, and the M. Eng. degree in computer engineering from the University of Campinas, Brazil in 2011, where he is a Ph. D. degree candidate. He currently holds the position of senior researcher in artificial intelligence at Research Department of Ericsson, Brazil.

His research interests include distributed systems, networked robotics, IoT and the applicability of different AI and machine learning techniques in such scenarios.

E-mail: ricardo.s.souza@ericsson.com

Silvia Lins received the B. Eng. degree in computer engineering and the M. Eng. degree in electrical engineering at the Federal University of Para, Brazil in 2011 and 2013, where she is a Ph. D. degree candidate. She is currently a researcher at Research Department of Ericsson, Brazil.

Her research interests include network architecture and protocols area, machine learning applied to congestion control algorithms and 5G use cases focused on equipment inspection through computer vision.

E-mail: silvia.lins@ericsson.com

Maria Marquezini received the M. Sc. and D. Sc. degrees in physics from the State University of Campinas (UNICAMP), Brazil in 1990 and 1995, respectively, From 1995 to 1997, she was a postdoctoral researcher with the Lawrence Berkeley National Laboratory (LBNL), Materials Science Division, conducting research activities in the field of electronic processes in semiconductors. From 1997 to 1999, she was an associate researcher with the Physics Institute, UNICAMP. Since 2000, she has been with Research Department of Ericsson, Brazil. She is currently responsible for coordinating research projects developed in partnership with universities and research institutes in Brazil. She is also a project manager from Ericsson side in the H2020 5G Range project, where Ericsson is leading one of the workpackages.

Her research interests include telecommunications domain, ranging from fixed to wireless technologies, and devices to networks technologies.

E-mail: maria.marquezini@ericsson.com

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Reis, G., Dantas, M., Bezerra, D. et al. Gripper Design for Radio Base Station Autonomous Maintenance System. Int. J. Autom. Comput. 18, 645–653 (2021). https://doi.org/10.1007/s11633-021-1300-5

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