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    <title>Avinash Singh</title>
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      <title>About Me</title>
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      <description>Introduction     Robotics Software and Controls Engineer. I&amp;rsquo;m passionate about everything robotics.
Github: avs2805 | Résumé: Google Drive
Skills     Programming: C++, Python, MATLAB/Simulink, Bash/Shell
Platforms: Linux, Windows, MacOS
Libraries/Tools: Robot Operating System (ROS), OpenCV, SciPy, NumPy, Scikit-Learn, Tensorflow
Version Control: Git
Sensors: Wheel encoders, IMU, LiDAR, Stereo Cameras, UWB (ultrawide band)
Boards/IPCs: Arduino, Raspberry Pi, STM Discovery Board, Jetson Nano, Jetson Tx2, Jetson Xavier</description>
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      <title>Publications</title>
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      <description>2020 Chukewad, Y. M., James, J., Singh, A., &amp;amp; Fuller, S. RoboFly: An insect-sized robot with simplified fabrication that is capable of flight, ground, and water surface locomotion. [arXiv preprint]
  2019 A. Singh, T. Libby, and S. B. Fuller, &amp;ldquo;Rapid Inertial Reorientation of an Aerial Insect-sized Robot Using a Piezo-actuated Tail,&amp;rdquo; in International Conference on Robotics and Automation (ICRA), 2019 IEEE/RSJ [PDF]
  2018 Chukewad, Y.</description>
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      <title>Simplified 1-D Kalman Filter</title>
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      <description>Variable Naming Convention     $x_t$​: state
$z_t$: measurement
$u_t$​: control action
Mean Calculation     $\mu$: Mean of the prior belief
$\sigma^{2}$: Variance of the prior belief
$\nu$: Mean of the measurement
$r^{2}$: Variance of the measurement
Measurement update Formulas     The new mean is calculated as a weighted sum of the prior belief and measurement means.
$$\mu&#39;=\frac{r^2\mu+\sigma^2\nu}{r^2+\sigma^2}$$
The new variance can be calculated as:</description>
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      <description>If you would like to get in touch with me, the best way would be via E-mail or Linkedin.
Email: avs2805@gmail.com | LinkedIn: Profile</description>
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