Araştırma Makalesi
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Mermi yörüngesi üzerindeki doğrusal ve doğrusal olmayan etkili faktörlerin sayısal analizi

Yıl 2025, Cilt: 12 Sayı: 23, 18 - 38

Mohammad Zia Zahedi , Mohammad Ali Sultani

Öz

Robotik sistemler kullanarak mermileri yakalamak, robotik araştırmalarda önemli zorluklar ortaya çıkarmaktadır. Mermi yörüngesini anlamak ve hareketini etkileyen temel faktörleri belirlemek, bu alandaki temel görevlerdir. Bu çalışma, bir mermi hareketini etkileyen faktörleri kapsamlı bir şekilde analiz etmeyi amaçlamaktadır ve özellikle ping pong topunun yörüngesine odaklanmaktadır. Yerçekimi, kaldırma kuvveti, santrifüj kuvveti gibi doğrusal faktörler ve hava direnci, Coriolis kuvveti gibi doğrusal olmayan faktörler incelenmektedir. Ping pong topunun hareket denklemleri, MATLAB programlaması kullanılarak sayısal ve analitik yöntemlerle çözülmektedir. Çalışma, bu önemli faktörlerin topun hareketi ve yörüngesi üzerindeki etkisini yüzdelik olarak belirlemektedir. Her bir faktörün katkısını anlayarak, mermi davranışıyla ilgili daha doğru ve kapsamlı bir anlayış elde edilebilir. Mermi ile hedefin çarpışma noktasını belirlemek için, yörünge eğrisinin üzerine oturan bir yaklaşık bir parabolik eğri denklemi elde edilir. Bu denklem, hedefle kesin çarpışma noktasının tahmininde değerli bir içgörü sağlar. Önerilen yöntem, analitik ve sayısal hesaplamalardan elde edilen sonuçların karşılaştırılması ve detaylı analizi yoluyla doğrulanmıştır. Bu araştırmanın bulguları, görüntü tabanlı gözetim sistemleri, spor video görüntülerinin analizi, insan faaliyetlerinin izlenmesi ve insan-makine etkileşimini geliştirmek gibi çeşitli alanlarda geniş uygulamalara sahiptir. Mermi hareketini etkileyen tüm önemli faktörleri dikkate alarak ve inceleyerek, bu araştırma, mermilerin doğru ve verimli bir şekilde yakalanması için değerli içgörüler ve araçlar sunarak robotik araştırmaların ilerlemesine katkıda bulunmaktadır.

Anahtar Kelimeler

Doğrusal olmayan denklemler projektil hareketinin dinamikleri hava direnci kaldırma kuvveti sayısal yöntem

Kaynakça

  • Alonso, M., & Finn, E. J. (1967). Fundamental university physics (Vol. 2, pp. p-818). Reading, MA: Addison-Wesley.
  • Anderson, J. D. (2017). Fundamentals of aerodynamics (6th ed.). McGraw-Hill Education.
  • Batchelor, G. K. (2000). An introduction to fluid dynamics. Cambridge university press.
  • Bäuml, B., Wimböck, T., & Hirzinger, G. (2010, October). Kinematically optimal catching a flying ball with a hand-arm-system. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2592-2599). IEEE.
  • Bohg, J., Morales, A., Asfour, T., & Kragic, D. (2014). Data-driven grasp synthesis—A survey. IEEE Transactions on Robotics, 30(2), 289–309.
  • Brancazio, P. J. (1985). Sport science: Physical laws and optimum performance. Simon & Schuster.
  • Cigliano, P., Lippiello, V., Ruggiero, F., & Siciliano, B. (2015). Robotic ball catching with an eye-in-hand single-camera system. IEEE Transactions on Control Systems Technology, 23(5), 1657-1671.
  • Çengel, Y. A., & Ghajar, A. J. (2011). Heat and Mass Transfer: Fundamentals and applications, 4th The McGraw-Hill Companies. Inc., New York, NY.
  • Dickhoff W. H. Projectile Motion with Air Resistance. Retrieved 11 14, 2023, from https://web.physics.wustl.edu/~wimd/topic01.pdf
  • Elger, D. F., LeBret, B. A., Crowe, C. T., & Roberson, J. A. (2020). Engineering fluid mechanics. John Wiley & Sons.
  • Frese, U., Bauml, B., Haidacher, S., Schreiber, G., Schäfer, I., Hahnle, M., & Hirzinger, G. (2001, October). Off-the-shelf vision for a robotic ball catcher. In Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No. 01CH37180) (Vol. 3, pp. 1623-1629). IEEE.
  • Goldstein, H., Poole, C., & Safko, J. (2001). Classical mechanics (3rd ed.). Addison-Wesley.
  • Greenwood, D. T. (2003). Advanced dynamics. Cambridge University Press.
  • Halliday, D., Resnick, R., & Walker, J. (2013). Fundamentals of physics. John Wiley & Sons.
  • Hong, W., & Slotine, J. J. E. (2005, June). Experiments in hand-eye coordination using active vision. In Experimental Robotics IV: The 4th International Symposium, Stanford, California, June 30–July 2, 1995 (pp. 130-139). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Kao, S. T., & Ho, M. T. (2021). Ball-catching system using image processing and an omni-directional wheeled mobile robot. Sensors, 21(9), 3208.
  • Kao, S. T., Wang, Y., & Ho, M. T. (2017, June). Ball catching with omni-directional wheeled mobile robot and active stereo vision. In 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE) (pp. 1073-1080). IEEE.
  • Kim, S., Shukla, A., & Billard, A. (2014).Catching objects in flight. IEEE Transactions on Robotics, 30(5), 1049-1065.
  • Koval, M. C., King, J. E., Pollard, N. S., & Srinivasa, S. S. (2015, September). Robust trajectory selection for rearrangement planning as a multi-armed bandit problem. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 2678-2685). IEEE.
  • Lai, H. Y., & Ke, H. Y. (2019). Projectile flight trajectory and position estimation system based on stereo vision. Sensors and Materials, 31(11), 3483-3493.
  • Lippiello, V., Ruggiero, F., & Siciliano, B. (2013). 3D monocular robotic ball catching. Robotics and Autonomous Systems, 61(12), 1615-1625.
  • Nagurka, M. L. (2003). Aerodynamic effects in a dropped ping-pong ball experiment. International Journal of Engineering Education.
  • Nathan, A. M. (2008). The effect of spin on the flight of a baseball. American Journal of Physics, 76(2), 119–124.
  • Nobahar, B., Shoaran, M., & Khosroshahi, G. K. (2020). Ball trajectory estimation and robot control to reach the ball using single camera. Journal of Control, 14(3), 75-87.
  • Oka, T., Komura, N., & Namiki, A. (2017, October). Ball juggling robot system controlled by high-speed vision. In 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS) (pp. 91-96). IEEE.
  • Park, G. R., Kim, K., Kim, C., Jeong, M. H., You, B. J., & Ra, S. (2009, September). Human-like catching motion of humanoid using evolutionary algorithm (ea)-based imitation learning. In RO-MAN 2009-The 18th IEEE International Symposium on Robot and Human Interactive Communication (pp. 809-815). IEEE.
  • Parker, G. W. (1977). Projectile motion with air resistance quadratic in the speed. American Journal of Physics, 45(7), 606-610.
  • Press, W. H. (2007). Numerical recipes 3rd edition: The art of scientific computing. Cambridge university press.
  • Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You only look once: Unified, real-time object detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779–788.
  • Riley, M., & Atkeson, C. G. (2002). Robot catching: Towards engaging human-humanoid interaction. Autonomous Robots, 12, 119-128.
  • Tian, J. D., Sun, J., & Tang, Y. D. (2011). Short-baseline binocular vision system for a humanoid ping-pong robot. Journal of Intelligent & Robotic Systems, 64, 543-560.
  • Xie, Q., Liu, Y., Xiong, R., & Chu, J. (2014, May). Real-time accurate ball trajectory estimation with “asynchronous” stereo camera system for humanoid Ping-Pong robot. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (pp. 6212-6217). IEEE.
  • Zhang, Z., Cui, Z., Xu, C., Yan, Y., Sebe, N., & Yang, J. (2020). Pattern-affinitive propagation across depth, surface normal and semantic segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(10), 3601–3614.

Analysis of linear and non-linear effective factors on the projectile trajectory

Yıl 2025, Cilt: 12 Sayı: 23, 18 - 38

Mohammad Zia Zahedi , Mohammad Ali Sultani

Öz

Catching projectiles using robotic systems poses significant challenges in robotics research. Understanding the projectile's trajectory and identifying the key factors influencing its movement are fundamental tasks in this field. This study aims to comprehensively analyze the factors affecting the motion of a projectile, specifically focusing on the trajectory of a ping pong ball. Both linear factors, such as gravity, buoyancy force, and centrifugal force, and nonlinear factors like air drag and Coriolis force, are examined. The motion equations of the ping pong ball are solved using numerical and analytical methods implemented in MATLAB programming. The study quantifies the percentage impact of these significant factors on the ball's motion and trajectory. By understanding the contributions of each factor, a more accurate and comprehensive understanding of the projectile's behavior can be achieved. To determine the point of impact of the projectile with the target, an equation of a fitted parabolic curve above the trajectory curve is obtained. This equation provides valuable insights into predicting the precise point of impact with the target. The proposed method is confirmed through the comparison and detailed analysis of the results obtained from analytical and numerical calculations. The findings of this research have broad applications in various fields, including image-based surveillance systems, analysis of sports video images, monitoring human activities, and enhancing human-machine interaction. By considering and studying all significant factors affecting projectile motion, this research contributes to the advancement of robotics research, providing valuable insights and tools for catching projectiles accurately and efficiently.

Anahtar Kelimeler

Nonlinear equations dynamics of projectile motion air drag buoyancy force numerical method

Kaynakça

  • Alonso, M., & Finn, E. J. (1967). Fundamental university physics (Vol. 2, pp. p-818). Reading, MA: Addison-Wesley.
  • Anderson, J. D. (2017). Fundamentals of aerodynamics (6th ed.). McGraw-Hill Education.
  • Batchelor, G. K. (2000). An introduction to fluid dynamics. Cambridge university press.
  • Bäuml, B., Wimböck, T., & Hirzinger, G. (2010, October). Kinematically optimal catching a flying ball with a hand-arm-system. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2592-2599). IEEE.
  • Bohg, J., Morales, A., Asfour, T., & Kragic, D. (2014). Data-driven grasp synthesis—A survey. IEEE Transactions on Robotics, 30(2), 289–309.
  • Brancazio, P. J. (1985). Sport science: Physical laws and optimum performance. Simon & Schuster.
  • Cigliano, P., Lippiello, V., Ruggiero, F., & Siciliano, B. (2015). Robotic ball catching with an eye-in-hand single-camera system. IEEE Transactions on Control Systems Technology, 23(5), 1657-1671.
  • Çengel, Y. A., & Ghajar, A. J. (2011). Heat and Mass Transfer: Fundamentals and applications, 4th The McGraw-Hill Companies. Inc., New York, NY.
  • Dickhoff W. H. Projectile Motion with Air Resistance. Retrieved 11 14, 2023, from https://web.physics.wustl.edu/~wimd/topic01.pdf
  • Elger, D. F., LeBret, B. A., Crowe, C. T., & Roberson, J. A. (2020). Engineering fluid mechanics. John Wiley & Sons.
  • Frese, U., Bauml, B., Haidacher, S., Schreiber, G., Schäfer, I., Hahnle, M., & Hirzinger, G. (2001, October). Off-the-shelf vision for a robotic ball catcher. In Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No. 01CH37180) (Vol. 3, pp. 1623-1629). IEEE.
  • Goldstein, H., Poole, C., & Safko, J. (2001). Classical mechanics (3rd ed.). Addison-Wesley.
  • Greenwood, D. T. (2003). Advanced dynamics. Cambridge University Press.
  • Halliday, D., Resnick, R., & Walker, J. (2013). Fundamentals of physics. John Wiley & Sons.
  • Hong, W., & Slotine, J. J. E. (2005, June). Experiments in hand-eye coordination using active vision. In Experimental Robotics IV: The 4th International Symposium, Stanford, California, June 30–July 2, 1995 (pp. 130-139). Berlin, Heidelberg: Springer Berlin Heidelberg.
  • Kao, S. T., & Ho, M. T. (2021). Ball-catching system using image processing and an omni-directional wheeled mobile robot. Sensors, 21(9), 3208.
  • Kao, S. T., Wang, Y., & Ho, M. T. (2017, June). Ball catching with omni-directional wheeled mobile robot and active stereo vision. In 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE) (pp. 1073-1080). IEEE.
  • Kim, S., Shukla, A., & Billard, A. (2014).Catching objects in flight. IEEE Transactions on Robotics, 30(5), 1049-1065.
  • Koval, M. C., King, J. E., Pollard, N. S., & Srinivasa, S. S. (2015, September). Robust trajectory selection for rearrangement planning as a multi-armed bandit problem. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 2678-2685). IEEE.
  • Lai, H. Y., & Ke, H. Y. (2019). Projectile flight trajectory and position estimation system based on stereo vision. Sensors and Materials, 31(11), 3483-3493.
  • Lippiello, V., Ruggiero, F., & Siciliano, B. (2013). 3D monocular robotic ball catching. Robotics and Autonomous Systems, 61(12), 1615-1625.
  • Nagurka, M. L. (2003). Aerodynamic effects in a dropped ping-pong ball experiment. International Journal of Engineering Education.
  • Nathan, A. M. (2008). The effect of spin on the flight of a baseball. American Journal of Physics, 76(2), 119–124.
  • Nobahar, B., Shoaran, M., & Khosroshahi, G. K. (2020). Ball trajectory estimation and robot control to reach the ball using single camera. Journal of Control, 14(3), 75-87.
  • Oka, T., Komura, N., & Namiki, A. (2017, October). Ball juggling robot system controlled by high-speed vision. In 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS) (pp. 91-96). IEEE.
  • Park, G. R., Kim, K., Kim, C., Jeong, M. H., You, B. J., & Ra, S. (2009, September). Human-like catching motion of humanoid using evolutionary algorithm (ea)-based imitation learning. In RO-MAN 2009-The 18th IEEE International Symposium on Robot and Human Interactive Communication (pp. 809-815). IEEE.
  • Parker, G. W. (1977). Projectile motion with air resistance quadratic in the speed. American Journal of Physics, 45(7), 606-610.
  • Press, W. H. (2007). Numerical recipes 3rd edition: The art of scientific computing. Cambridge university press.
  • Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016). You only look once: Unified, real-time object detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 779–788.
  • Riley, M., & Atkeson, C. G. (2002). Robot catching: Towards engaging human-humanoid interaction. Autonomous Robots, 12, 119-128.
  • Tian, J. D., Sun, J., & Tang, Y. D. (2011). Short-baseline binocular vision system for a humanoid ping-pong robot. Journal of Intelligent & Robotic Systems, 64, 543-560.
  • Xie, Q., Liu, Y., Xiong, R., & Chu, J. (2014, May). Real-time accurate ball trajectory estimation with “asynchronous” stereo camera system for humanoid Ping-Pong robot. In 2014 IEEE International Conference on Robotics and Automation (ICRA) (pp. 6212-6217). IEEE.
  • Zhang, Z., Cui, Z., Xu, C., Yan, Y., Sebe, N., & Yang, J. (2020). Pattern-affinitive propagation across depth, surface normal and semantic segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(10), 3601–3614.
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Balistik Sistemleri, Makine Mühendisliğinde Sayısal Yöntemler
Bölüm Araştırma Makalesi
Yazarlar

Mohammad Zia Zahedi 0000-0002-0585-3753

Mohammad Ali Sultani 0000-0001-7711-6894

Erken Görünüm Tarihi 14 Temmuz 2025
Yayımlanma Tarihi
Gönderilme Tarihi 18 Kasım 2023
Kabul Tarihi 19 Nisan 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 12 Sayı: 23

Kaynak Göster

APA Zahedi, M. Z., & Sultani, M. A. (2025). Analysis of linear and non-linear effective factors on the projectile trajectory. Science and Technique in the 21st Century, 12(23), 18-38.
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