An embedded beamformer for a PID-based trajectory sensing for an autonomous vehicle

• Autorzy: Mvemba P. K. , Lay-Ekuakille A. , Kidiamboko S. , Rahman M. Z. U.

Identyfikatory

DOI

10.24425/123891

• Języki publikacji: EN

Abstrakty

EN

Beamforming is an advanced signal processing technique used in sensor arrays for directional signal transmission or reception. The paper deals with a system based on an ultrasound transmitter and an array of receivers, to determine the distance to an obstacle by measuring the time of flight and - using the phase beamforming technique to process the output signals of receivers for finding the direction from which the reflected signal is received - locates the obstacle. The embedded beam-former interacts with a PID-based line follower robot to improve performance of the line follower navigation algorithm by detecting and avoiding obstacles. The PID (proportional-integral-derivative) algorithm is also typically used to control industrial processes. It calculates the difference between a measured value and a desired set of points, then attempts to minimize the error by adjusting the output. The overall navigation system combines a PID-based trajectory follower with a spatial-temporal filter (beamformer) that uses the output of an array of sensors to extract signals received from an obstacle in a particular direction in order to guide an autonomous vehicle or a robot along a safe path.

Słowa kluczowe

EN

autonomous vehicle; beamforming; trajectory follower; ultrasonic obstacle detector; measurement; sensors

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2018
• Tom: Vol. 25, nr 3
• Strony: 561--575
• Opis fizyczny: Bibliogr. 23 poz., rys., wykr., wzory

Twórcy

autor

Mvemba P. K.

• University of Siena, Department of Information Engineering and Mathematics, 53100 Siena, Italy

autor

Lay-Ekuakille A.

• University of Salento, Department of Innovation Engineering, 73100 Lecce, Italy

autor

Kidiamboko S.

• ISTA University, Department of Electronics, Kinshasa, DR Congo

autor

Rahman M. Z. U.

• KL University, Department of E.C.E., Green Fields, Vaddeswaram, Guntur-522502, India

Bibliografia

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• [4] Ying, D., Songshu, S. (2002). Global Stability of the PD+Feedforward Robot Robust Adaptive control. ACTA Automatic Sinica, 8(1), 11-18.
• [5] Lay-Ekuakille, A., Vendramin, G., Trotta, A. (2008). Beamforming-Based Acoustic Imaging for Distance Retrieval. IMTC 2008 - IEEE International Instrumentation and Measurement Technology Conference, Victoria, Vancouver Island, Canada.
• [6] Jafarov, E.M., Parlakci M.N.A., Istefanopulos, Y. (2005). A new variable structure PID-controller design for robot manipulators. IEEE Transactions on Control Systems Technology, 13(1), 122-130.
• [7] Ramasamy, S., Pradhan, H.V., Ramanathan, P., Arulmozhivarman, P., Tatavarti, R. (2012). A novel and pedagogical approach to teach PID controller with LabVIEW signal express. IEEE International Conference on Engineering Education: Innovative Practices and Future Trends (AICERA), Kerala, India.
• [8] Amer, N.H., Hudha, K., Zamzuri, H., Aparow, V.R., Abidin, A.F.Z., Kadir, Z.A., Murrad, M. (2018). Adaptive modified Stanley controller with fuzzy supervisory system for trajectory tracking of an autonomous armoured vehicle. Robotics and Autonomous Systems, 105, 94-111.
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• [13] Lay-Ekuakille, A., Vergallo, P., Saracino, D., Trotta, A. (2012). Optimizing and post processing of a smart Beamformer forobstacle retrieval. IEEE Sensors Journal, 12(5), 1294-1299.
• [14] Grythe, J. (2010). Beamforming algorithms - beamformers. Norsonic AS, Oslo, Norway.
• [15] Johnson, D.H., Dudgeon, D.E. (1993). Array signal processing: concepts and techniques. P T R Prentice Hall.
• [16] Um, D., Sriraman, V. (2004). Teaching basic control systems theory using robots. Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition. Oregon, USA.
• [17] Van Trees, H.L. (2002). Detection, Estimation, and Modulation Theory, Optimum Array Processing. Part IV edition Ed. Wiley-Interscience. New York.
• [18] Strakowski, M.R., Kosmowski, B.B., Kowalik, R. (2006). An Ultrasonic Obstacle Detector Based on Phase Beamforming Principles. IEEE Sensors Journal, 6(1), 179-186.
• [19] Lay-Ekuakille, A., Palamara, I., Caratelli, D., Morabito, F.C. (2013). Experimental Infrared Measurements for Hydrocarbon Pollutant Determination in Subterranean Waters. Review of Scientific Instruments, 84, 015103-1.
• [20] Lay-Ekuakille, A., Trotta, A. (2011). Predicting VOC Concentration Measurements: Cognitive Approach for Sensor Networks. IEEE Sensors Journal, 11(11), 3923-3030.
• [21] Karthik, G.V.S., Fathima,Y., Zia Ur Rahman, M., Ahamed, R. (2013). Efficient Signal Conditioning techniques for Brain activity in Remote Health Monitoring Network. IEEE Sensors Journal, 13(9), 3276-3283.
• [22] Chahbi, I., Ben Amara, D., Belghith, A. (2013). A novel route guidance algorithm using beam-forming techniques for vehicular networks. Proceedings-Conference on Local Computer Networks, LCN2013, Sydney, Australia.
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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).