Paper Info
Title
Rosi: A Robotic System For Harsh Outdoor Industrial Inspection-System Design And Applications
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.
Year
DOI
Venue
2021
10.1007/s10846-021-01459-2
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
Keywords
DocType
Volume
Mobile manipulator design, Assisted operation control, Machine learning for industrial inspection, Belt conveyor inspection, Service robot
Journal
103
Issue
ISSN
Citations 
2
0921-0296
2
PageRank 
References 
Authors
0.50
0
18
Name
Order
Citations
PageRank
Filipe A. S. Rocha120.50
Gabriel Garcia220.50
Raphael F. S. Pereira320.50
Henrique D. Faria420.50
Thales H. Silva520.50
Ricardo H. R. Andrade620.50
Evelyn S. Barbosa720.50
André Almeida820.50
Emanuel Cruz920.50
Wagner Andrade1020.50
Wenderson Serrantola1120.50
Luiz Moura1220.50
Héctor Azpúrua1320.50
Andre Franca1420.50
Gustavo Pessin1516423.10
Gustavo Medeiros Freitas1621.18
Ramon R. Costa1710710.09
Fernando Lizarralde1822435.29