Deep learning and evolutionary algorithms for identification of aerodynamic parameters
Dynamic chess piece movement simulator using Control Lyapunov Functions (CLF) and Control Barrier Functions (CBF). Focused on path planning and obstacle avoidance, it explores non-traditional chess movements for robotics and game theory applications
This project develops a 5 Degree of Freedom (DOF) Robotic Arm engineered for high precision in pick-and-place tasks, ideal for applications ranging from manufacturing to research labs. The arm features advanced control systems and can handle objects with care, accuracy, and efficiency.
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