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NAO robot üzerindeki çalışmaların incelemesi

Year 2025, Volume: 14 Issue: 2, 1 - 1

Tuğba Kara , Ahmet Gökçen

Abstract

Robotlar birçok alanda insanların çeşitli iş yükünü azaltarak birçok yeni bilimsel alanı şekillendirmektedir. Bu inceleme, 2020-2024 yılları arasında insansı robot NAO üzerinde yapılan araştırma ve gelişmelere genel bir bakış sunmaktadır. Robotun fiziksel yapısından donanım ve yazılım bileşenlerine kadar genel bir incelemeyi kapsamaktadır. İnceleme, NAO ile ilgili çalışmaları üç ana alanda kategorize etmektedir: İnsan-Robot Etkileşimleri, Navigasyon ve Diğerleri. NAO robotundaki son gelişmelerin açıklanması, robotiğin geleceğindeki potansiyel ilerlemelerin daha derinlemesine anlaşılmasını kolaylaştırmayı amaçlamaktadır.

Keywords

Robotik NAO Robot İnsan Etkileşimi Navigasyon

References

  • NAO Robot Common Appearance https://www.aldebaran.com/themes/custom/softbank/images/full-nao.png, Accessed 1 March 2024.
  •    I. Trifirò, A. Augello, U. Maniscalco, G. Pilato and F. Vella, How are you? How a Robot can Learn to Express its own Roboceptions. Procedia Computer Science, 176, 480–489, 2020. https://doi.org/10.1016/j.procs.2020.08.050.
  •    T. Nama, S. Deb, B. Debnath and P. Kumari, Designing a humanoid robot integrated Exer-Learning-Interaction (ELI). Procedia Computer Science, 167, 1524–1532, 2020. https://doi.org/10.1016/j.procs.2020.03.363.
  •    D. Reforgiato Recupero and F. Spiga, Knowledge acquisition from parsing natural language expressions for humanoid robot action commands. Information Processing & Management, 57(6), 102094, 2020. https://doi.org/10.1016/j.ipm.2019.102094.
  •    R. Romero-García, R. Martínez-Tomás, P. Pozo, F. de la Paz and E. Sarriá, Q-CHAT-NAO: A robotic approach to autism screening in toddlers. Journal of Biomedical Informatics, 118, 103797, 2021. https://doi.org/10.1016/j.jbi.2021.103797.
  •    N. Efthymiou, P. P. Filntisis, P. Koutras, A. Tsiami, J. Hadfield, G. Potamianos and P. Maragos, ChildBot: Multi-robot perception and interaction with children. Robotics and Autonomous Systems, 150, 103975, 2022. https://doi.org/10.1016/j.robot.2021.103975.
  •    A. S. Ivani, A. Giubergia, L. Santos, A. Geminiani, S. Annunziata, A. Caglio, I. Olivieri and A. Pedrocchi, A gesture recognition algorithm in a robot therapy for ASD children. Biomedical Signal Processing and Control, 74, 103512, 2022. https://doi.org/10.1016/j.bspc.2022.103512.
  •    A. Håkansson and M. S. Amberkar, The Handie system: Hand signs interaction with autonomous, mobile cyber-physical systems. Procedia Computer Science, 207, 3681–3690, 2022. https://doi.org/10.1016/j.procs.2022.09.428.
  •    L. Morillo-Mendez, O. M. Mozos and M. G. S. Schrooten, Gaze cueing in older and younger adults is elicited by a social robot seen from the back. Cognitive Systems Research, 101149, 2023. https://doi.org/10.1016/j.cogsys.2023.101149.
  • H. Jeon, D.-W. Kim and B.-Y. Kang, Deep reinforcement learning for cooperative robots based on adaptive sentiment feedback. Expert Systems with Applications, 121198, 2023. https://doi.org/10.1016/j.eswa.2023.121198.
  • P. B. Kumar, M. K. Muni and D. R. Parhi, Navigational analysis of multiple humanoids using a hybrid regression-fuzzy logic control approach in complex terrains. Applied Soft Computing, 89, 106088, 2020. https://doi.org/10.1016/j.asoc.2020.106088.
  • A. K. Kashyap, D. R. Parhi, M. K. Muni and K. K. Pandey, A hybrid technique for path planning of humanoid robot NAO in static and dynamic terrains. Applied Soft Computing, 96, 106581, 2020. https://doi.org/10.1016/j.asoc.2020.106581.
  • J. García and D. Shafie, Teaching a humanoid robot to walk faster through Safe Reinforcement Learning. Engineering Applications of Artificial Intelligence, 88, 103360, 2020. https://doi.org/10.1016/j.engappai.2019.103360.
  • A. K. Kashyap and D. R. Parhi, Particle Swarm Optimization aided PID gait controller design for a humanoid robot. ISA Transactions, 2020. https://doi.org/10.1016/j.isatra.2020.12.033.
  • A. Kumar Kashyap, A. Pandey, D. R. Parhi and A. Sharma, Path optimization for multiple humanoid robot using TLBO based ANFIS controller in obscure environment. Materials Today: Proceedings, 2021. https://doi.org/10.1016/j.matpr.2021.02.756.
  • A. Kumar Kashyap and D. R. Parhi, Multi-objective trajectory planning of humanoid robot using hybrid controller for multi-target problem in complex terrain. Expert Systems with Applications, 179, 115110, 2021. https://doi.org/10.1016/j.eswa.2021.115110.
  • A. K. Kashyap, D. R. Parhi and A. Pandey, Multi-objective optimization technique for trajectory planning of multi-humanoid robots in cluttered terrain. ISA Transactions, 2021. https://doi.org/10.1016/j.isatra.2021.06.017.
  • M. Kasaei, M. Abreu, N. Lau, A. Pereira and L. P. Reis, Robust biped locomotion using deep reinforcement learning on top of an analytical control approach. Robotics and Autonomous Systems, 146, 103900, 2021. https://doi.org/10.1016/j.robot.2021.103900.
  • A. K. Kashyap and D. R. Parhi, Implementation of intelligent navigational techniques for inter-collision avoidance of multiple humanoid robots in complex environment. Applied Soft Computing, 109001, 2022. https://doi.org/10.1016/j.asoc.2022.109001.
  • P. Mishra, U. Jain, S. Choudhury, S. Singh, A. Pandey, A. Sharma, R. Singh, V. K. Pathak, K. K. Saxena and A. Gehlot, Footstep planning of humanoid robot in ROS environment using Generative Adversarial Networks (GANs) deep learning. Robotics and Autonomous Systems, 104269, 2022. https://doi.org/10.1016/j.robot.2022.104269.
  • A. K. Kashyap, A. Pandey, D. R. Parhi and S. Singh Gour, Trajectory tracking of single and multiple humanoid robots in cluttered environment. Materials Today: Proceedings, 56, 650–654, 2022. https://doi.org/10.1016/j.matpr.2021.12.558.
  • M. K. Muni, D. R. Parhi, P. B. Kumar, C. Sahu and S. Kumar, Towards motion planning of humanoids using a fuzzy embedded neural network approach. Applied Soft Computing, 119, 108588, 2022. https://doi.org/10.1016/j.asoc.2022.108588.
  • Vikas, D. R. Parhi and A. K. Kashyap, Humanoid robot path planning using memory-based gravity search algorithm and enhanced differential evolution approach in a complex environment. Expert Systems with Applications, 215, 119423, 2023. https://doi.org/10.1016/j.eswa.2022.119423.
  • Vikas and D. R. Parhi, Chaos-based optimal path planning of humanoid robot using hybridized regression-gravity search algorithm in static and dynamic terrains. Applied Soft Computing, 110236, 2023. https://doi.org/10.1016/j.asoc.2023.110236.
  • D. Coquin, R. Boukezzoula, A. Benoit and T. L. Nguyen, Assistance via IoT networking cameras and evidence theory for 3D object instance recognition: Application for the NAO humanoid robot. Internet of Things, 9, 100128, 2020. https://doi.org/10.1016/j.iot.2019.100128.
  • P. A. Akiki, P. A. Akiki, A. K. Bandara and Y. Yu, EUD-MARS: End-user development of model-driven adaptive robotics software systems. Science of Computer Programming, 200, 102534, 2020. https://doi.org/10.1016/j.scico.2020.102534.
  • F. Riccio, R. Capobianco and D. Nardi, LoOP: Iterative learning for optimistic planning on robots. Robotics and Autonomous Systems, 136, 103693, 2021. https://doi.org/10.1016/j.robot.2020.103693.
  • A. Grillo, S. Carpin, C. T. Recchiuto and A. Sgorbissa, Trust as a metric for auction-based task assignment in a cooperative team of robots with heterogeneous capabilities. Robotics and Autonomous Systems, 157, 104266, 2022. https://doi.org/10.1016/j.robot.2022.104266.
  • M. Naya-Varela, A. Faíña and R. J. Duro, Engineering morphological development in a robotic bipedal walking problem: An empirical study. Neurocomputing, 527, 83–99, 2023. https://doi.org/10.1016/j.neucom.2023.01.003.
  • A. Botta, S. Rotbei, S. Zinno and G. Ventre, Cyber security of robots: A comprehensive survey. Intelligent Systems With Applications, 18, 200237, 2023. https://doi.org/10.1016/j.iswa.2023.200237.
  • A. Augello, S. Gaglio, I. Infantino, U. Maniscalco, G. Pilato and F. Vella, Roboception and adaptation in a cognitive robot. Robotics and Autonomous Systems, 164, 104400, 2023. https://doi.org/10.1016/j.robot.2023.104400.
  • P.-H. Kuo and K.-L. Chen, Two-stage fuzzy object grasping controller for a humanoid robot with proximal policy optimization. Engineering Applications of Artificial Intelligence, 125, 106694, 2023. https://doi.org/10.1016/j.engappai.2023.106694.

Review of studies on NAO robot

Year 2025, Volume: 14 Issue: 2, 1 - 1

Tuğba Kara , Ahmet Gökçen

Abstract

Robots are reducing the various workload of humans in numerous fields, shaping many new scientific areas. This review provides an overview of research and developments conducted on the humanoid robot NAO between the years 2020 and 2024. It encompasses a general examination from the robot's physical structure to its hardware and software components. The review categorizes studies related to NAO into three main areas: Human-Robot Interactions, Navigation, and Others. The explanation of recent developments in NAO robot aims to facilitate a deeper understanding of potential advancements in the future of robotics.

Keywords

NAO Robot Robotics Human Interaction Navigation

References

  • NAO Robot Common Appearance https://www.aldebaran.com/themes/custom/softbank/images/full-nao.png, Accessed 1 March 2024.
  •    I. Trifirò, A. Augello, U. Maniscalco, G. Pilato and F. Vella, How are you? How a Robot can Learn to Express its own Roboceptions. Procedia Computer Science, 176, 480–489, 2020. https://doi.org/10.1016/j.procs.2020.08.050.
  •    T. Nama, S. Deb, B. Debnath and P. Kumari, Designing a humanoid robot integrated Exer-Learning-Interaction (ELI). Procedia Computer Science, 167, 1524–1532, 2020. https://doi.org/10.1016/j.procs.2020.03.363.
  •    D. Reforgiato Recupero and F. Spiga, Knowledge acquisition from parsing natural language expressions for humanoid robot action commands. Information Processing & Management, 57(6), 102094, 2020. https://doi.org/10.1016/j.ipm.2019.102094.
  •    R. Romero-García, R. Martínez-Tomás, P. Pozo, F. de la Paz and E. Sarriá, Q-CHAT-NAO: A robotic approach to autism screening in toddlers. Journal of Biomedical Informatics, 118, 103797, 2021. https://doi.org/10.1016/j.jbi.2021.103797.
  •    N. Efthymiou, P. P. Filntisis, P. Koutras, A. Tsiami, J. Hadfield, G. Potamianos and P. Maragos, ChildBot: Multi-robot perception and interaction with children. Robotics and Autonomous Systems, 150, 103975, 2022. https://doi.org/10.1016/j.robot.2021.103975.
  •    A. S. Ivani, A. Giubergia, L. Santos, A. Geminiani, S. Annunziata, A. Caglio, I. Olivieri and A. Pedrocchi, A gesture recognition algorithm in a robot therapy for ASD children. Biomedical Signal Processing and Control, 74, 103512, 2022. https://doi.org/10.1016/j.bspc.2022.103512.
  •    A. Håkansson and M. S. Amberkar, The Handie system: Hand signs interaction with autonomous, mobile cyber-physical systems. Procedia Computer Science, 207, 3681–3690, 2022. https://doi.org/10.1016/j.procs.2022.09.428.
  •    L. Morillo-Mendez, O. M. Mozos and M. G. S. Schrooten, Gaze cueing in older and younger adults is elicited by a social robot seen from the back. Cognitive Systems Research, 101149, 2023. https://doi.org/10.1016/j.cogsys.2023.101149.
  • H. Jeon, D.-W. Kim and B.-Y. Kang, Deep reinforcement learning for cooperative robots based on adaptive sentiment feedback. Expert Systems with Applications, 121198, 2023. https://doi.org/10.1016/j.eswa.2023.121198.
  • P. B. Kumar, M. K. Muni and D. R. Parhi, Navigational analysis of multiple humanoids using a hybrid regression-fuzzy logic control approach in complex terrains. Applied Soft Computing, 89, 106088, 2020. https://doi.org/10.1016/j.asoc.2020.106088.
  • A. K. Kashyap, D. R. Parhi, M. K. Muni and K. K. Pandey, A hybrid technique for path planning of humanoid robot NAO in static and dynamic terrains. Applied Soft Computing, 96, 106581, 2020. https://doi.org/10.1016/j.asoc.2020.106581.
  • J. García and D. Shafie, Teaching a humanoid robot to walk faster through Safe Reinforcement Learning. Engineering Applications of Artificial Intelligence, 88, 103360, 2020. https://doi.org/10.1016/j.engappai.2019.103360.
  • A. K. Kashyap and D. R. Parhi, Particle Swarm Optimization aided PID gait controller design for a humanoid robot. ISA Transactions, 2020. https://doi.org/10.1016/j.isatra.2020.12.033.
  • A. Kumar Kashyap, A. Pandey, D. R. Parhi and A. Sharma, Path optimization for multiple humanoid robot using TLBO based ANFIS controller in obscure environment. Materials Today: Proceedings, 2021. https://doi.org/10.1016/j.matpr.2021.02.756.
  • A. Kumar Kashyap and D. R. Parhi, Multi-objective trajectory planning of humanoid robot using hybrid controller for multi-target problem in complex terrain. Expert Systems with Applications, 179, 115110, 2021. https://doi.org/10.1016/j.eswa.2021.115110.
  • A. K. Kashyap, D. R. Parhi and A. Pandey, Multi-objective optimization technique for trajectory planning of multi-humanoid robots in cluttered terrain. ISA Transactions, 2021. https://doi.org/10.1016/j.isatra.2021.06.017.
  • M. Kasaei, M. Abreu, N. Lau, A. Pereira and L. P. Reis, Robust biped locomotion using deep reinforcement learning on top of an analytical control approach. Robotics and Autonomous Systems, 146, 103900, 2021. https://doi.org/10.1016/j.robot.2021.103900.
  • A. K. Kashyap and D. R. Parhi, Implementation of intelligent navigational techniques for inter-collision avoidance of multiple humanoid robots in complex environment. Applied Soft Computing, 109001, 2022. https://doi.org/10.1016/j.asoc.2022.109001.
  • P. Mishra, U. Jain, S. Choudhury, S. Singh, A. Pandey, A. Sharma, R. Singh, V. K. Pathak, K. K. Saxena and A. Gehlot, Footstep planning of humanoid robot in ROS environment using Generative Adversarial Networks (GANs) deep learning. Robotics and Autonomous Systems, 104269, 2022. https://doi.org/10.1016/j.robot.2022.104269.
  • A. K. Kashyap, A. Pandey, D. R. Parhi and S. Singh Gour, Trajectory tracking of single and multiple humanoid robots in cluttered environment. Materials Today: Proceedings, 56, 650–654, 2022. https://doi.org/10.1016/j.matpr.2021.12.558.
  • M. K. Muni, D. R. Parhi, P. B. Kumar, C. Sahu and S. Kumar, Towards motion planning of humanoids using a fuzzy embedded neural network approach. Applied Soft Computing, 119, 108588, 2022. https://doi.org/10.1016/j.asoc.2022.108588.
  • Vikas, D. R. Parhi and A. K. Kashyap, Humanoid robot path planning using memory-based gravity search algorithm and enhanced differential evolution approach in a complex environment. Expert Systems with Applications, 215, 119423, 2023. https://doi.org/10.1016/j.eswa.2022.119423.
  • Vikas and D. R. Parhi, Chaos-based optimal path planning of humanoid robot using hybridized regression-gravity search algorithm in static and dynamic terrains. Applied Soft Computing, 110236, 2023. https://doi.org/10.1016/j.asoc.2023.110236.
  • D. Coquin, R. Boukezzoula, A. Benoit and T. L. Nguyen, Assistance via IoT networking cameras and evidence theory for 3D object instance recognition: Application for the NAO humanoid robot. Internet of Things, 9, 100128, 2020. https://doi.org/10.1016/j.iot.2019.100128.
  • P. A. Akiki, P. A. Akiki, A. K. Bandara and Y. Yu, EUD-MARS: End-user development of model-driven adaptive robotics software systems. Science of Computer Programming, 200, 102534, 2020. https://doi.org/10.1016/j.scico.2020.102534.
  • F. Riccio, R. Capobianco and D. Nardi, LoOP: Iterative learning for optimistic planning on robots. Robotics and Autonomous Systems, 136, 103693, 2021. https://doi.org/10.1016/j.robot.2020.103693.
  • A. Grillo, S. Carpin, C. T. Recchiuto and A. Sgorbissa, Trust as a metric for auction-based task assignment in a cooperative team of robots with heterogeneous capabilities. Robotics and Autonomous Systems, 157, 104266, 2022. https://doi.org/10.1016/j.robot.2022.104266.
  • M. Naya-Varela, A. Faíña and R. J. Duro, Engineering morphological development in a robotic bipedal walking problem: An empirical study. Neurocomputing, 527, 83–99, 2023. https://doi.org/10.1016/j.neucom.2023.01.003.
  • A. Botta, S. Rotbei, S. Zinno and G. Ventre, Cyber security of robots: A comprehensive survey. Intelligent Systems With Applications, 18, 200237, 2023. https://doi.org/10.1016/j.iswa.2023.200237.
  • A. Augello, S. Gaglio, I. Infantino, U. Maniscalco, G. Pilato and F. Vella, Roboception and adaptation in a cognitive robot. Robotics and Autonomous Systems, 164, 104400, 2023. https://doi.org/10.1016/j.robot.2023.104400.
  • P.-H. Kuo and K.-L. Chen, Two-stage fuzzy object grasping controller for a humanoid robot with proximal policy optimization. Engineering Applications of Artificial Intelligence, 125, 106694, 2023. https://doi.org/10.1016/j.engappai.2023.106694.
There are 32 citations in total.

Details

Primary Language English
Subjects Social Robotics, Intelligent Robotics, Assistive Robots and Technology
Journal Section Articles
Authors

Tuğba Kara 0009-0007-7038-1995

Ahmet Gökçen 0000-0002-7569-5447

Early Pub Date March 17, 2025
Publication Date
Submission Date July 9, 2024
Acceptance Date December 27, 2024
Published in Issue Year 2025 Volume: 14 Issue: 2

Cite

APA Kara, T., & Gökçen, A. (2025). Review of studies on NAO robot. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 14(2), 1-1. https://doi.org/10.28948/ngumuh.1509692
AMA Kara T, Gökçen A. Review of studies on NAO robot. NOHU J. Eng. Sci. March 2025;14(2):1-1. doi:10.28948/ngumuh.1509692
Chicago Kara, Tuğba, and Ahmet Gökçen. “Review of Studies on NAO Robot”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 14, no. 2 (March 2025): 1-1. https://doi.org/10.28948/ngumuh.1509692.
EndNote Kara T, Gökçen A (March 1, 2025) Review of studies on NAO robot. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 14 2 1–1.
IEEE T. Kara and A. Gökçen, “Review of studies on NAO robot”, NOHU J. Eng. Sci., vol. 14, no. 2, pp. 1–1, 2025, doi: 10.28948/ngumuh.1509692.
ISNAD Kara, Tuğba - Gökçen, Ahmet. “Review of Studies on NAO Robot”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 14/2 (March 2025), 1-1. https://doi.org/10.28948/ngumuh.1509692.
JAMA Kara T, Gökçen A. Review of studies on NAO robot. NOHU J. Eng. Sci. 2025;14:1–1.
MLA Kara, Tuğba and Ahmet Gökçen. “Review of Studies on NAO Robot”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, vol. 14, no. 2, 2025, pp. 1-1, doi:10.28948/ngumuh.1509692.
Vancouver Kara T, Gökçen A. Review of studies on NAO robot. NOHU J. Eng. Sci. 2025;14(2):1-.

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