Quantitative Analysis of Ant Motion Using Video Tracking: Evidence of Quasi-Harmonic Oscillatory Behavior
DOI:
https://doi.org/10.33394/j-lkf.v14i1.19593Keywords:
Ant motion, Video tracking, Oscillatory motion, Tracker, Quasi-harmonic motionAbstract
The motion of living organisms, including insects, often appears irregular and complex, making it difficult to describe using simple physical models. Nevertheless, certain biological movements may contain periodic components that can be approximated using basic motion models in physics. This study aims to analyze the movement of an ant using video tracking with the Tracker software to investigate whether its motion exhibits characteristics related to simple harmonic motion (SHM). Motion data were obtained from a recorded video with a frame rate of 20 fps and processed to determine the two-dimensional position projected onto a one-dimensional displacement axis, from which velocity and acceleration were derived using Tracker. The displacement–time analysis shows quasi-periodic fluctuations that can be approximated by a sinusoidal function with an amplitude of approximately 0.042 m and a frequency of about 0.21 Hz. The acceleration–displacement relationship shows a general negative trend consistent with the tendency predicted by SHM, although deviations from ideal linearity are observed. In addition, the velocity–displacement phase diagram does not form a clear elliptical pattern, indicating that the motion does not strictly follow ideal SHM behavior. These findings suggest that ant locomotion exhibits quasi-harmonic characteristics influenced by biological locomotion mechanisms and environmental interactions, demonstrating that video-based motion analysis provides a quantitative approach for examining oscillatory components in natural biological motion.
References
Anfinogentov, S., & Nakariakov, V. (2016). Motion magnification in coronal seismology. Solar Physics, 291(11), 3251–3267. https://doi.org/10.1007/s11207-016-1013-z
Arroyave-Tobón, S., Ramírez, C., & Vélez, D. (2022). Oscillatory dynamics in microscale motion: A sinusoidal modeling approach. Biological Cybernetics, 116(3), 241–254.
Bochynek, T., Dell, A. I., & others. (2017). Kinematics and behavioral analysis of small insect motion using high-resolution imaging. Methods in Ecology and Evolution, 8, 1234–1242.
Chen, L., Huang, M., & Takeda, K. (2021). Applying sinusoidal motion models to describe rhythmic locomotion in micro-organisms. Physical Review E, 104(3), Article 034408. https://doi.org/10.1103/PhysRevE.104.034408
Chong, Z. (2022). A qualitative analysis to simple harmonic motion. arXiv. http://arxiv.org/abs/2209.12662
Deeti, R., Kadam, P., & Provini, P. (2023). Inter-leg coordination and sensory feedback in walking insects: Emergence of oscillatory locomotion patterns. Journal of Insect Physiology, 149, Article 104559. https://doi.org/10.1016/j.jinsphys.2023.104559
Dell, A. I., Bender, J. A., & others. (2014). Movement patterns in small organisms: Integrating behavior and environment. Ecology Letters, 17, 1402–1410.
Eme, S., Kadam, R., & Provini, P. (2023). Oscillatory patterns in small organism locomotion: Quantitative analysis using sinusoidal modeling under micro-environmental variability. Journal of Experimental Biology, 226(7), Article jeb245612. https://doi.org/10.1242/jeb.245612
Feeny, B., Sternberg, P., Cronin, C., & Coppola, C. (2013). Complex orthogonal decomposition applied to nematode posturing. Journal of Computational and Nonlinear Dynamics, 8(4). https://doi.org/10.1115/1.4023548
Halliday, D., Resnick, R., & Walker, J. (2013). Fundamentals of physics (10th ed.). Wiley.
Jeyasingh-Jacob, J., Crook-Rumsey, M., Shah, H., Joseph, T., Abulikemu, S., Daniels, S., Sharp, D. J., & Haar, S. (2024). Markerless motion capture to quantify functional performance in neurodegeneration: Systematic review. JMIR Aging, 7. https://doi.org/10.2196/52582
Kadam, P., Fang, G., & Zou, J. J. (2024). Object tracking using computer vision: A review. Computers, 13(6). https://doi.org/10.3390/computers13060136
Karuru, P., Silka, B., Gela, M., Pakiding, A., & Lolang, E. (2023). Students’ response to the use of Tracker software in physics laboratory. Journal of Research and Community Service, 4(11), 2178–2184. http://devotion.greenvest.co.id
Palacios-Vargas, A. G., Hernández, J. L., Soto, M., & Díaz, R. (2021). Characterization of locomotion patterns in small insects using motion tracking and harmonic analysis. Journal of Experimental Biology, 224(14), Article jeb242156. https://doi.org/10.1242/jeb.242156
Provini, P., Camp, A. L., & Crandell, K. E. (2023). Emerging biological insights enabled by high-resolution 3D motion data: Promises, perspectives and pitfalls. Journal of Experimental Biology, 226. https://doi.org/10.1242/jeb.245138
Sabattini, J. A., Sturniolo, F., Bollazzi, M., & Bugnon, L. A. (2023). AntTracker: A low-cost and efficient computer vision approach to research leaf-cutter ants behavior. Smart Agricultural Technology, 5, Article 100252. https://doi.org/10.1016/j.atech.2023.100252
Serway, R. A., & Jewett, J. W. (2014). Physics for scientists and engineers (9th ed.). Cengage Learning.
Wee, L. K., & Leong, T. K. (2015). Using Tracker to promote active learning in kinematics. Physics Education, 50(4), 409–413.
Wu, B., Xu, Y., Zhou, G., & Fan, Y. (2024). Computer-based experiment for the motion of spring oscillator on a linear air track using ultrasonic sensor. Sensors, 24(14). 4441. https://doi.org/10.3390/s24144441
Wu, M., Cao, X., Cao, X., & Guo, S. (2017). A dataset of ant colonies motion trajectories in indoor and outdoor scenes for social cluster behavior study. GigaScience. http://arxiv.org/abs/2204.04380
Wu, M., Cao, X., & Guo, S. (2022). Swarm behavior tracking based on a deep vision algorithm. Frontiers, 1–18. http://arxiv.org/abs/2204.03319
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