Binh Nguyen

Binh Nguyen

Experienced Researcher with a demonstrated history of working on Machine Learning, Robotics and Controls. Skilled in Mathematical Modeling and Embedded Systems.

Differentiable Programming

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Model predictive contouring control

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Let us consider kinematics of the racing car

$$\begin{align} x_{t+1} = f_p(x_t, u_t;\zeta_p) = \begin{bmatrix} X_t + \Delta_T v_t \cos \phi_t, \\ Y_t + \Delta_T v_t \sin \phi_t, \\ \phi_t + \Delta_T \omega_t, \\ v_t + \Delta_T \zeta_p a_t, \end{bmatrix} \end{align}$$

where \(\zeta_p \in (0,1]\), \(\Delta_T = 0.05[s]\) is the slipping coefficient which depends position of the racing car in the track (or road). Denote by \(x_t = [X_t, Y_t, \phi_t, v_t]^\top\), \(u_t = [\omega_t, a_t]^\top\) the state of the racing car at current time step \(t\).

Informative Path Planning

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

UAV control

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