Design of a vision‐based autonomous turret

• Autorzy: Louali Rabah , Negadi Djilali , Hamadouche Rabah , Nemra Abdelkrim

Identyfikatory

DOI

10.14313/JAMRIS/4-2022/35

• Języki publikacji: EN

Abstrakty

EN

This article describes the hardware and software de‐ sign of a vision‐based autonomous turret system. A two degree of freedom (2 DOF) turret platform is designed to carry a cannon equipped with an embedded camera and actuated by stepper motors or direct current motors. The turret system includes a central calculator running a visual detection and tracking solution, and a microcon‐ troller, responsible for actuators control. The Tracking‐ Learning‐Detection (TLD) algorithm is implemented for target detection and tracking. Furthermore, a Kalman filter algorithm is implemented to continue the tracking in case of occlusion. The performances of the designed turret, regarding response time, accuracy and the execu‐ tion time of its main tasks, are evaluated. In addition, an experimental scenario was performed for real‐time autonomous detection and tracking of a moving target.

Słowa kluczowe

EN

autonomous turret; stepper motor; DC motor; vision based control; Tracking‐Learning‐Detection algorithm; TLD algorithm; Kalman based visual tracking

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2022
• Tom: Vol. 16, No. 4
• Strony: 72--77
• Opis fizyczny: Bibliogr. 6 poz., rys.

Twórcy

autor

Louali Rabah

• Ecole Militaire Polytechnique, Algeria.

autor

Negadi Djilali

• Ecole Militaire Polytechnique, Algeria.

autor

Hamadouche Rabah

• Ecole Militaire Polytechnique, Algeria.

autor

Nemra Abdelkrim

• Ecole Militaire Polytechnique, Algeria.

Bibliografia

• [1] R. R. Alcala, Z. G. Arceo, J. N. Baterisna, J. O. Morada, J. O. D. Ramirez, and R. E. Tolentino, “Design and implementation of body wearable device and oculus rift controlled panning and aiming sentry gun turret”. 2020 4th Interna‑tional Conference on Trends in Electronics and Informatics (ICOEI)(48184), 2020, pp. 871–876, 10.1109/ICOEI48184.2020.9143032.
• [2] A. Guersenzvaig, “Autonomous weapon systems: Failing the principle of discrimination”, IEEE Tech‑nology and Society Magazine, vol. 37, no. 1, 2018, pp. 55–61, 10.1109/MTS.2018.2795119.
• [3] Z. Kalal, K. Mikolajczyk, and J. Matas, “Tracking‑learning‑detection”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 7, 2012, pp. 1409–1422.
• [4] R. E. Kalman, “A New Approach to Linear Filtering and Prediction Problems”, Journal of Basic Engineering, vol. 82, no. 1, 1960, pp. 35–45, 10.1115/1.3662552.
• [5] S. Kuswadi, M. N. Tamara, and D. N. H.W., “Gun turret automatic weapon control system design and realization”. 2016 International Symposium on Electronics and Smart Devices (ISESD), 2016, pp. 30–34.
• [6] M. Tsourma and M. Dasygenis, “Development of a hybrid defensive embedded system with face recognition”. 2016 IEEE Intl Conference on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and Applications for Business Engineering (DCABES), 2016, pp. 154–157.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).