Evaluating the Suitability of Several AR Devices and Tools for Industrial Applications

被引:2
作者
Battegazzorre, Edoardo [1 ]
Calandra, Davide [1 ]
Strada, Francesco [1 ]
Bottino, Andrea [1 ]
Lamberti, Fabrizio [1 ]
机构
[1] Politecn Torino, Dipartimento Automat & Informat, Turin, Italy
来源
AUGMENTED REALITY, VIRTUAL REALITY, AND COMPUTER GRAPHICS, AVR 2020, PT II | 2020年 / 12243卷
关键词
Augmented Reality; Industrial Augmented Reality; Evaluation; Marker detection; Positional tracking; VIRTUAL-REALITY;
D O I
10.1007/978-3-030-58468-9_19
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent years, there has been an increasing interest in Industrial Augmented Reality (IAR) due to its prominent role in the ongoing revolution known as Industry 4.0. For companies and industries it is essential to evaluate carefully which of the developed AR-based technologies to adopt, and when, for tasks such as training, maintenance, assistance, and collaborative design. There is also a wide array of hardware and software alternatives on the market, characterized by a significant heterogeneity in terms of functionalities, performance and cost. With this work, our objective is to study and compare some widely available devices and Software Development Kits (SDKs) for AR by leveraging a set of evaluation criteria derived from the actual literature which have been deemed capable to qualify the above assets as suitable for industrial applications. Such criteria include the operative range, robustness, accuracy and stability. Both marker-based and marker-less solutions have been considered, in order to investigate a wide range of possible use cases.
引用
收藏
页码:248 / 267
页数:20
相关论文
共 13 条
[1]   A Practical Evaluation of Commercial Industrial Augmented Reality Systems in an Industry 4.0 Shipyard [J].
Blanco-Novoa, Oscar ;
Fernandez-Carames, Tiago M. ;
Fraga-Lamas, Paula ;
Vilar-Montesinos, Miguel A. .
IEEE ACCESS, 2018, 6 :8201-8218
[2]  
De Pace F., 2018, AM J COMPUTER SCI IN, V6, P17, DOI DOI 10.21767/2349-3917.100017
[3]   A survey of industrial augmented reality [J].
de Souza Cardoso, Luis Fernando ;
Queiroz Mariano, Flavia Cristina Martins ;
Zorzal, Ezequiel Roberto .
COMPUTERS & INDUSTRIAL ENGINEERING, 2020, 139
[4]  
Duenser A., 2008, ACM SIGGRAPH ASIA 20
[5]   Generation of fiducial marker dictionaries using Mixed Integer Linear Programming [J].
Garrido-Jurado, S. ;
Munoz-Salinas, R. ;
Madrid-Cuevas, F. J. ;
Medina-Carnicer, R. .
PATTERN RECOGNITION, 2016, 51 :481-491
[6]   A training system for Industry 4.0 operators in complex assemblies based on virtual reality and process mining [J].
Jesus Roldan, Juan ;
Crespo, Elena ;
Martin-Barrio, Andres ;
Pena-Tapia, Elena ;
Barrientos, Antonio .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2019, 59 :305-316
[7]   General Requirements for Industrial Augmented Reality Applications [J].
Knoke, Moritz Quandta Benjamin ;
Knoke, Benjamin ;
Gorldt, Christian ;
Freitag, Michael ;
Thoben, Klaus-Dieter .
51ST CIRP CONFERENCE ON MANUFACTURING SYSTEMS, 2018, 72 :1130-1135
[8]   Mixed reality in production and logistics: Discussing the application potentials of Microsoft HoloLens™ [J].
Lang, Sebastian ;
Kota, Mohammed Saif Sheikh Dastagir ;
Weigert, David ;
Behrendt, Fabian .
ICTE IN TRANSPORTATION AND LOGISTICS 2018 (ICTE 2018), 2019, 149 :118-129
[9]   Realizing Virtual Reality Learning Environment for Industry 4.0 [J].
Liagkou, Vasiliki ;
Salmas, Dimitrios ;
Stylios, Chrysostomos .
12TH CIRP CONFERENCE ON INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING, 2019, 79 :712-717
[10]   Adopting augmented reality in the age of industrial digitalisation [J].
Masood, Tariq ;
Egger, Johannes .
COMPUTERS IN INDUSTRY, 2020, 115