İnsansız kara aracı geliştirmeye bütünleşik bir yaklaşım: tasarım, analiz ve gerçekleştirme

Ömer Cihan Kıvanç, Tahir Eren Mungan, Berkin Atila, Gürkan Tosun
329 38

Öz


Akıllı araç kavramının elektrikli araçlar ile ivme kazanması ve sonrasında otonom araç teknolojilerine olan ilginin artmasıyla birlikte insansız kara aracı (İKA) çalışmaları ve yatırımları hız kazanmaktadır.  İnsansız kara araçları karmaşık bir yapıya ve teknolojiye sahip olmalarına rağmen, kullanımlarıyla beraber birçok avantajı beraberlerinde getirmektedirler. İnsana özgü özelliklere sahip olmaması (uyku, yorgunluk, sinir vb.), insandan çok daha hızlı tepki verebilmesi ve koşullara göre tüm olasılıkları hesaplayarak mantıksal olarak en doğru kararı seçebilmesi İKA’ların en önemli avantajıdır. Yapılan çalışmada kendi kendine belirli ya da belirsiz bir bölgede ilerleyebilecek yetiye sahip, haritalandırma, konumlandırma, yörünge belirleme ve takibi, engellerin yerini saptama ve bu engellerle çarpışmayı önleyecek yeni yol arama özelliklerine sahip bir İKA geliştirilmiştir. Belirli bir harita, kroki veya kat planı bulunmayan bir arazide; İKA’nın açık alanda GPS, kapalı alanda lidar, IMU ve enkoder verileri ile otonom sürüş gerçekleştirme kabiliyeti yapılan deneyler ile doğrulanmıştır. Çalışmada İKA tasarımı için gereksinim duyulan aşamalar, problemler, çözüm teknikleri ve sonuçlar belirli bir yaklaşım ile sunulmuştur.


Anahtar kelimeler


İnsansız kara araçları; Yörünge takibi; Eş zamanlı konum belirleme ve haritalandırma; Kinematik Modelleme; Sezgisel yol arama

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Referanslar


Bacik J., Durovsky F., Biro M., Kyslan K, Perdukova D., Padmanaban S., Pathfinder–development of automated guided vehicle for hospital logistics, IEEE Access, 5, 26892-26900, 2017.

Luettel T., Himmelsbach M., Wuensche H., Autonomous ground vehicles: concepts and a path to the future, Proc. IEEE, 100, 1831-1839, 2012.

Dickmanns E.D., Developing the sense of vision for autonomous road vehicles at UniBwM, Computer, 50 (12), 24-31, 2017.

Bimbraw K., Autonomous cars: Past, Present and Future a review of the Developments in the Last Century, the Present Scenario and the Expected Future of Autonomous Vehicle Technology, 12th International Conference on Informatics in Control, Automation and Robotics, Colmar, France, 21-23 July 2015.

Maxwell P., Larkin D., Lowrance C., Turning remote-controlled military systems into autonomous force multipliers, IEEE Potentials, 32 (6), 39-43, 2013.

Weiskircher T., Wang Q., Ayalew B., Predictive guidance and control framework for (semi-) autonomous vehicles in public traffic, IEEE Trans. Control Syst. Technol., 25 (6), 2034-2046, 2017.

Young S.H., Mazzuchi T.A., Sarkani S., A framework for predicting future system performance in autonomous unmanned ground vehicles, IEEE Trans. Syst. Man Cybern., 47 (7), 1192-1206, 2017.

Karlsson R., Gustafsson F., The future of automotive localization algorithms: available, reliable, and scalable localization: anywhere and anytime, IEEE Signal Process Mag., 34 (2), 60-69, 2017.

Broggi A., Buzzoni M., Debattisti S., Grisleri P., Laghi M.C., Medici P., Versari P., Extensive tests of autonomous driving technologies, IEEE Trans. Intell. Transp. Syst., 14 (3), 1403-1415, 2013.

Balcılar M., Yavuz S., Amasyalı M.F., Uslu E., Çakmak F., R-SLAM: Resilient localization and mapping in challenging environments, Rob. Auton. Syst., 87, 66-80, 2017.

Yoon S., Yoon S., Lee U., Shim D.H., Recursive path planning using reduced states for car-like vehicles on grid maps, IEEE Trans. Intell. Transp. Syst., 16 (5), 2797-2813, 2015.

Qian J., Zi B., Wang D., Ma Y., Zhang D., The design and development of an omni-directional mobile robot oriented to an intelligent manufacturing system, Sensors, 17 (2073), 1-15, 2017.

Kayacan E., Ramon H., Saeys W., Robust trajectory tracking error model-based predictive control for unmanned ground vehicles, IEEE/ASME Trans. Mechatron., 21 (2), 806-814, 2016.

Andreasson H., Bouguerra A., Cirillo M., Dimitrov D.N., Driankov D., Karlsson L., Lilienthal A.J., Pecora F., Saarinen J.P., Sherikov A., Stoyanov T., Autonomous transport vehicles: where we are and what is missing, IEEE Rob. Autom. Mag., 22 (1), 64-75, 2015.

Muir P.F., Neuman C.P., Kinematic modeling for feedback control of an omnidirectional wheeled mobile robot, IEEE International Conference on Robotics and Automation , Raleigh, USA, 6 July 1987.

Laliberte T., Gosselin C.M., Cote G., Practical prototyping: a rapid prototyping framework for fast and cost-effective design of robotic mechanism prototypes, IEEE Rob. Autom. Mag., 8 (3), 43-53, 2001.

Viboonchaicheep P., Shimada A., Kosaka Y., Position Rectification Control for Mecanum Wheeled Omni-Directional Vehicles, The 29th Annual Conference of the IEEE Industrial Electronics Society, Roanoke, VA, USA, 2-6 Nov. 2003.

Abouzahir M., Elouardi A., Latif R., Bouaziz S., Tajer A., Embedding SLAM algorithms: has it come of age?, Robotics and Autonomous Systems, Rob. Auton. Syst., 100, 14-26, 2018.

Navaravong L., Kan Z., Shea J.M., Dixon W.E., Formation reconfiguration for mobile robots with network connectivity constraints, IEEE Network, 26 (4), 18-24, 2012.

Aoyama M., Computing for the next-generation automobile, Computer, 45 (6), 32-37, 2012.

Silva O.D., Mann G.K.I, Gosine R.G., An ultrasonic and vision-based relative positioning sensor for multirobot localization, IEEE Sens. J., 15 (3), 1716-1726, 2015.

Wyglinski A.M., Huang X., Padir T., Lai L., Eisenbarth T.R., Venkatasubramanian K., Security of autonomous systems employing embedded computing and sensors, IEEE Micro, 33 (1), 80-86, 2013.

Tsai C.C., Wu H.L., Nonsingular Terminal Sliding Control Using Fuzzy Wavelet Networks for Mecanum Wheeled Omni-Directional Vehicles, IEEE International Conference on Fuzzy Systems, Barcelona, Spain, 18-23 July 2010.

Tlale N., Villiers M.D., Kinematics and Dynamics Modelling of a Mecanum Wheeled Mobile Platform, 15th International Conference on Mechatronics and Machine Vision in Practice, Auckland, New Zealand, 2-4 Dec. 2008.

Zhao D., Deng X., Yi J., Motion and internal force control for omnidirectional wheeled mobile robots, IEEE/ASME Trans. Mechatron., 14 (3), 382-387, 2009.

Atila B., Mungan T.E., Kivanc O.C., Different Filter Approaches and Performance Analysis of Fundamental Sensors in Autonomous Ground Vehicles, 24th Signal Processing and Communication Application Conference, Zonguldak, Turkey, 16-19 May 2016.

Gomez-Gil J., Ruiz-Gonzalez R., Alonso-Garcia S., Gomez-Gil F.J., A kalman filter implementation for precision improvement in low-cost GPS positioning of tractors, Sensors, 13 (11), 15307-15323, 2013.

Hidayat A.A., Arief Z., Happyanto D.C., Mobile Application With Simple Moving Average Filtering for Monitoring Finger Muscles Therapy of Post-Stroke People, International Electronics Symposium, Surabaya, Indonesia, 29-30 Sept. 2015.

Hui X.F., Wu Y.J., Research on Simple Moving Average Trading System Based on SVM, International Conference on Management Science and Engineering, Dallas, TX, USA, 20-22 Sept. 2012.

Demosthenous P., Nicolaou, N., Georgiou J., A Hardware-Efficient Lowpass Filter Design for Biomedical Applications, IEEE Biomedical Circuits and Systems Conference, Paphos, Cyprus, 3-5 Nov. 2010.

Widrow B., Adaptive filters, Aspects Netw. Syst. Theory, 563-586, 1971.

Bresson G., Alsayed Z., Yu L., Glaser S., Simultaneous localization and mapping: a survey of current trends in autonomous driving, IEEE Trans. Intell. Veh., 2 (3), 194-220, 2017.

Cadena C., Carlone L., Carrillo H., Latif Y., Scaramuzza D., Neira J., Reid I., Leonard J.J., Past, present, and future of simultaneous localization and mapping: toward the robust-perception age, IEEE Trans. Rob., 32 (6), 1309-1332, 2016.

Temeltas H., Kavak D., SLAM for robot navigation, IEEE A&E Syst. Mag., 23 (12), 16-19, 2008.

Karaoğuz H., Erkent Ö., Bayram H., Bozma I., Tek robottan çoklu robotlara ortam haritalama, EMO Bilimsel Dergi, 2 (4), 105-118, 2012.

Khan S., Wollherr D., Buss M., Modeling laser intensities for simultaneous localization and mapping, IEEE Rob. Autom. Lett., 1 (2), 692-699, 2016.

Shen S., Michael N., Kumar V., Obtaining liftoff indoors: autonomous navigation in confined indoor environments, IEEE Rob. Autom. Mag., 20 (4), 40-48, 2013.

Wang J., Zhang X., Gao Q., Ma X., Feng X., Wang H., Device-free simultaneous wireless localization and activity recognition with wavelet feature, IEEE Trans. Veh. Technol., 66 (2), 1659-1669, 2017.

Dine A., Elouardi A., Vincke B., Bouaziz S., Graph-based simultaneous localization and mapping: computational complexity reduction on a multicore heterogeneous architecture, IEEE Rob. Autom. Mag., 23 (4), 160-173, 2016.

Golan Y., Edelman S., Shapiro A., Rimon E., Online robot navigation using continuously updated artificial temperature gradients, IEEE Rob. Autom. Lett., 2 (3), 1280-1287, 2017.

Wang X., Zhang C., Liu F., Dong Y., Xu X., Exponentially weighted particle filter for simultaneous localization and mapping based on magnetic field measurements, IEEE Trans. Instrum. Meas., 66 (7), 1658-1667, 2017.

Shiozaki T., Dissanayake G., Eliminating scale drift in monocular SLAM using depth from defocus, IEEE Rob. Autom. Lett., 3 (1), 581-587, 2018.

Sun Q., Yuan J., Zhang X., Sun F., RGB-D SLAM in indoor environments with STING-based plane feature extraction, IEEE/ASME Trans. Mechatron., PP (99), 2017.

Santos J.M., Portugal D., Rocha R.P., An Evaluation of 2D SLAM Techniques Available in Robot Operating System, IEEE International Symposium on Safety, Security, and Rescue Robotics, Linkoping, Sweden, 21-26 Oct. 2013.

Kohlbrecher S., Stryk O.V., Meyer J., Klingauf U., A Flexible and Scalable SLAM System With Full 3D Motion Estimation, IEEE International Symposium on Safety, Security, and Rescue Robotics, Kyoto, Japan, 1-5 Nov. 2011.

Choi H., Yang K.W., Kim E., Simultaneous global localization and mapping, IEEE/ASME Trans. Mechatron., 19 (4), 1160-1170, 2014.

Karamat T.B., Lins R.G., Givigi S.N., Noureldin A., Novel EKF-based vision/inertial system integration for improved navigation, IEEE Trans. Instrum. Meas., 67 (1), 116-125, 2018.

Huang S., Dissanayake G., Convergence and consistency analysis for extended kalman filter based SLAM, IEEE Trans. Rob., 23 (5), 1036-1049, 2007.

Hu C., Wang R., Yan F., Chen N., Output constraint control on path following of four-wheel independently actuated autonomous ground vehicles, IEEE Trans. Veh. Technol., 65 (6), 4033-4043, 2016.

Hajjaji A.E., Bentalba S., Fuzzy path tracking control for automatic steering of vehicles, Rob. Auton. Syst., 43 (4), 203-213, 2003.

Lenain R., Thuilot B., Cariou C., Martinet P., High accuracy path tracking for vehicles in presence of sliding: Application to farm vehicle automatic guidance for agricultural tasks, Auton. Robot, 21 (1), 79-97, 2006.

Wang R., Hu C., Yan F., Chadli M., Composite nonlinear feedback control for path following of four-wheel independently actuated autonomous ground vehicles, IEEE Trans. Intell. Transp. Syst., 17 (7), 2063-2074, 2016.

Yoon S., Yoon S.E., Lee U., Shim D.H., Recursive path planning using reduced states for car-like vehicles on grid maps, IEEE Trans. Intell. Transp. Syst., 16 (5), 2797-2813, 2015.

Wang Y., Li X., Ruiz R., An exact algorithm for the shortest path problem with position-based learning effects, IEEE Trans. Syst. Man Cybern., 47 (11), 3037-3049, 2017.

Lin M., Yuan K., Shi C., Wang Y., Path Planning of Mobile Robot Based on Improved A∗ Algorithm, 29th Chinese Control And Decision Conference, Chongqing, China, 28-30 May 2017.

Silva J.B.B., Siebra C.A., Nascimento T.P., A New Cost Function Heuristic Applied to A* Based Path Planning in Static and Dynamic Environments, 12th Latin American Robotics Symposium, Uberlandia, Brazil, 29-31 Oct. 2015.

Ozguner U., Acarman T., Redmill K., Autonomous Ground Vehicles, Artech Theory, 201-215, 2011.

Ge S.S., Lewis F.L., Autonomous Mobile Robots: Sensing, Control, Decision Making and Applications, Taylor & Francis Group, 2006.




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