Embodied Voice Assistant Markup Language

  • Marcelo Marques da Rocha UFF
  • Débora Christina Muchaluat Saade UFF

Resumo


Due to advances in robotics, the complexity of robots has increased greatly, allowing these devices to be used in increasingly challenging tasks. As a result, there is an increase in the complexity of developing programs for these robots, especially when using general purpose languages (GPLs). Even in simple programs this difficulty persists, as the algorithms need to communicate with sensors, obtaining and processing their values and, after processing, send some command to the robot’s actuators. In order to facilitate the programming of interactive sessions for social robotics platforms, this work proposes Embodied Voice Assistant Markup Language, a domain specific language based on XML, which can be applied to different social robots. The proposed language has elements for creating and manipulating variables, generating random numbers and conditional controls. In addition, it also proposes command abstractions for controlling multimodal interaction elements that are important in the human-robot interaction process. The Goal Question Metric paradigm (GQM) was used to structure the language assessment with 12 software developers, and then analyzed its clarity, effectiveness and perceived ease of use. This exploratory work presented very promising results, providing evidence that the proposed language is easy to use and understand.
Palavras-chave: Robot programming language, XML, Human–robot interaction, Social robot

Referências

Angelos Amanatiadis, Vasileios G Kaburlasos, Christina Dardani, Savvas A Chatzichristofis, and Athanasios Mitropoulos. 2020. Social robots in special education: Creating dynamic interactions for optimal experience. IEEE Consumer Electronics Magazine 9, 3 (2020), 39–45

J-C Baillie. 2005. Urbi: Towards a universal robotic low-level programming language. In 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 820–825

Victor R Basili. 1992. Software Modeling and Measurement: The Goal Question Metric Paradigm, CS-TR-2956. (UMIACS-TR-92-96) (9 1992)

John Brooke. 1996. SUS-A quick and dirty usability scale. Usability evaluation in industry 189, 194 (1996), 4–7

Victor R Basili1 Gianluigi Caldiera and H Dieter Rombach. 1994. The Goal Question Metric Approach. Encyclopedia of Software Engineering (1994), 528–532

Yaofei Chen, Rose Dios, Ali Mili, Lan Wu, and Kefei Wang. 2005. An empirical study of programming language trends. IEEE software 22, 3 (2005), 72–79

Dagoberto Cruz-Sandoval and Jesus Favela. 2019. A Conversational Robot to Conduct Therapeutic Interventions for Dementia. IEEE Pervasive Computing 18, 2 (2019), 10–19. https://doi.org/10.1109/MPRV.2019.2907020

Marcelo Marques da Rocha, Dagoberto Cruz-Sandoval, Jesus Favela, and Débora C Muchaluat-Saade. 2022. An Open-Source Socially Assistive Robot for Multisensory Healthcare Therapies. In Proceedings of the 2nd Workshop on Multisensory Experiences-SensoryX’22. SBC

Joan DiPietro, Arpad Kelemen, Yulan Liang, and Cecilia Sik-Lanyi. 2019. Computer-and robot-assisted therapies to aid social and intellectual functioning of children with autism spectrum disorder. Medicina 55, 8 (2019), 440

Jorien Hendrix and Emilia Barakova. 2020. Can Social Robots Actually be Used in Special Education? Designing an Easy to Use and Customizable Game for Robot Therapy for Children with Autism. Complex Control Systems Vol 2 (2020), 20–25

Eka Prasetyo Herwidodo, Ahmad Zaini, 2015. INI framework: Indonesian language interpreter software for controlling Nao robot movement. In 2015 International Seminar on Intelligent Technology and Its Applications (ISITIA). IEEE, 63–68

Martha Jiménez, Alberto Ochoa, Daniela Escobedo, Ricardo Estrada, Erwin Martinez, Rocío Maciel, and Víctor Larios. 2019. Recognition of Colors through Use of a Humanoid Nao Robot in Therapies for Children with Down Syndrome in a Smart City. Res. Comput. Sci 148 (2019), 239–252

Rensis Likert. 1932. A technique for the measurement of attitudes.Archives of psychology (1932)

Nikola Marangunić and Andrina Granić. 2015. Technology acceptance model: a literature review from 1986 to 2013. Universal access in the information society 14, 1 (2015), 81–95

Marcelo Marques da Rocha, Dagoberto Cruz-Sandoval, Jesus Favela, and Débora C. Muchaluat-Saade. 2022. EvaSIM: a Software Simulator for the EVA Open-source Robotics Platform. In 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). 714–721. https://doi.org/10.1109/RO-MAN53752.2022.9900561

M. Marques da Rocha and D. C. Muchaluat-Saade. 2023. Friendly Robot for Education and Healthcare: FRED. In Proceedings of LIQUE - Life Improvement in Quality by Ubiquitous Experiences Workshop, together with ACM IMX 2023

Marjan Mernik, Jan Heering, and Anthony M Sloane. 2005. When and how to develop domain-specific languages. ACM computing surveys (CSUR) 37, 4 (2005), 316–344.

Gavin Nicol, Lauren Wood, Mike Champion, and Steve Byrne. 2001. Document object model (DOM) level 3 core specification. W3C Working Draft 13 (2001), 1–146

Alexandra Q Nilles, Mattox Beckman, Chase Gladish, and Amy LaViers. 2018. Improv: Live coding for robot motion design. In Proceedings of the 5th International Conference on Movement and Computing. 1–6.

Carlo Pinciroli and Giovanni Beltrame. 2016. Buzz: a programming language for robot swarms. IEEE Software 33, 4 (2016), 97–100

Martin Schrepp, Andreas Hinderks, and Jörg Thomaschewski. 2017. Construction of a Benchmark for the User Experience Questionnaire (UEQ). International Journal of Interactive Multimedia and Artificial Intelligence 4, 4 (2017), 40

Shyamli Suneesh and Virginia Ruiz Garate. 2022. An Overview of Socially Assistive Robotics for Special Education. In International Conference on Social Robotics. Springer, 183–193

Steve Tousignant, Eric Van Wyk, and Maria Gini. 2011. An overview of XRobots: A hierarchical state machine-based language. (2011)

Biel Piero E Alvarado Vasquez and Fernando Matia. 2019. A social robot empowered with a new programming language and its performance in a laboratory. In 2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA). IEEE, 1–6

Shuo Yang, Xinjun Mao, Binbin Ge, and Sen Yang. 2015. The roadmap and challenges of robot programming languages. In 2015 IEEE International Conference on Systems, Man, and Cybernetics. IEEE, 328–333.
Publicado
23/10/2023
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DA ROCHA, Marcelo Marques; MUCHALUAT SAADE, Débora Christina. Embodied Voice Assistant Markup Language. In: SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 29. , 2023, Ribeirão Preto/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 246–254.