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    Home»Artificial Intelligence»Predicting a Ball Trajectory. Polynomial Fit in Python with NumPy | by Florian Trautweiler | Jan, 2025
    Artificial Intelligence

    Predicting a Ball Trajectory. Polynomial Fit in Python with NumPy | by Florian Trautweiler | Jan, 2025

    Team_AIBS NewsBy Team_AIBS NewsJanuary 5, 2025No Comments1 Min Read
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    Polynomial Slot in Python with NumPy

    Towards Data Science

    Ball Monitoring and Trajectory Prediction

    In a earlier challenge I visualized the trajectory of a ball that I threw vertically into the air with a real-time place, velocity and acceleration plot. Extending upon this challenge, I needed to calculate and visualize a trajectory prediction based mostly on a easy physics mannequin. On this put up, I’ll clarify how I match the mannequin to the measured state of the ball and visualize the anticipated trajectory.

    Place, Velocity and Acceleration Plots with Prediction

    Let’s begin with the physics mannequin for the ball. For simplicity, I’m solely contemplating the vertical motion of the ball, simplifying the issue to a one-dimensional one. Moreover, I’m solely modelling the ball as quickly because it leaves my hand and neglecting any air drag. This merely leaves us with a single fixed power performing on the ball: gravity.

    Gravitational Power performing on the Ball

    The power is calculated with the mass of the ball and the gravitational acceleration g, which is roughly 9.8m/s², relying on location and altitude. The…



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