We focus on controlling fish behavior, specifically aiming to manipulate the movements of fish shoals and guide them toward desired patterns or locations. This research involves developing algorithms that leverage the natural dynamics of fish shoals, applying principles such as collective behavior, environmental stimuli, and external influences. We are exploring a wide range of applications, including ecological studies, underwater robotics, and resource management.
第8回計測自動制御学会制御部門マルチシンポジウム
M. Ogura and N. Wakamiya, “Reduced order model predictive control of a fish schooling model,” 第8回計測自動制御学会制御部門マルチシンポジウム, pp. 3D2-1, 2021.
References
| [3] | M. Ogura and N. Wakamiya, “Reduced-order model predictive control of a fish schooling model,” Nonlinear Analysis: Hybrid Systems, vol. 49, p. 101342, 2023. [ DOI | arXiv | http ] |
| [2] | M. Ogura and N. Wakamiya, “Model predictive control of fish schooling model with reduced-order prediction model,” in 60th IEEE Conference on Decision and Control, 2021, pp. 4115-4120. [ DOI | http ] |
| [1] | M. Ogura and N. Wakamiya, “Reduced order model predictive control of a fish schooling model,” 第8回計測自動制御学会制御部門マルチシンポジウム, pp. 3D2-1, 2021. [ http ] |