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Mobile Robot Navigation Based on Embedded Computer Vision

Author

Listed:
  • Alberto Marroquín

    (Escuela de Ingeniería Eléctrica, Pontificia Universidad Católica de Valparaíso, Av. Brasil 2147, Valparaíso 2362804, Chile)

  • Gonzalo Garcia

    (Escuela de Ingeniería Eléctrica, Pontificia Universidad Católica de Valparaíso, Av. Brasil 2147, Valparaíso 2362804, Chile)

  • Ernesto Fabregas

    (Departamento de Informática y Automática, Universidad Nacional de Educación a Distancia, Juan del Rosal 16, 28040 Madrid, Spain)

  • Ernesto Aranda-Escolástico

    (Departamento de Ingeniería de Software y Sistemas Informáticos, Universidad Nacional de Educación a Distancia, Juan del Rosal 16, 28040 Madrid, Spain)

  • Gonzalo Farias

    (Escuela de Ingeniería Eléctrica, Pontificia Universidad Católica de Valparaíso, Av. Brasil 2147, Valparaíso 2362804, Chile)

Abstract

The current computational advance allows the development of technological solutions using tools, such as mobile robots and programmable electronic systems. We present a design that integrates the Khepera IV mobile robot with an NVIDIA Jetson Xavier NX board. This system executes an algorithm for navigation control based on computer vision and the use of a model for object detection. Among the functionalities that this integration adds to the Khepera IV in generating guided driving are trajectory tracking for safe navigation and the detection of traffic signs for decision-making. We built a robotic platform to test the system in real time. We also compared it with a digital model of the Khepera IV in the CoppeliaSim simulator. The navigation control results show significant improvements over previous works. This is evident in both the maximum navigation speed and the hit rate of the traffic sign detection system. We also analyzed the navigation control, which achieved an average success rate of 93 % . The architecture allows testing new control techniques or algorithms based on Python, facilitating future improvements.

Suggested Citation

  • Alberto Marroquín & Gonzalo Garcia & Ernesto Fabregas & Ernesto Aranda-Escolástico & Gonzalo Farias, 2023. "Mobile Robot Navigation Based on Embedded Computer Vision," Mathematics, MDPI, vol. 11(11), pages 1-17, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2561-:d:1163120
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    References listed on IDEAS

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    1. Jian Sun & Jie Zhao & Xiaoyang Hu & Hongwei Gao & Jiahui Yu, 2023. "Autonomous Navigation System of Indoor Mobile Robots Using 2D Lidar," Mathematics, MDPI, vol. 11(6), pages 1-21, March.
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    Cited by:

    1. Lu Chen & Gun Li & Weisi Xie & Jie Tan & Yang Li & Junfeng Pu & Lizhu Chen & Decheng Gan & Weimin Shi, 2024. "A Survey of Computer Vision Detection, Visual SLAM Algorithms, and Their Applications in Energy-Efficient Autonomous Systems," Energies, MDPI, vol. 17(20), pages 1-38, October.

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