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diplodocuslongus's Projects

freeimu-updates icon freeimu-updates

IMU - FreeIMU Library Zero Drift, Altitude & LSM303 Heading Stability

funmirrors icon funmirrors

This is a fun project I created to motivate computer vision enthusiasts and to highlight the importance of understanding fundamental concepts related to image formation in a camera.

geophone icon geophone

Code and Arduino shield for a frequency analyzer for geometric sensors

gnss-ins-sim icon gnss-ins-sim

Open-source GNSS + inertial navigation, sensor fusion simulator. Motion trajectory generator, sensor models, and navigation

gnuradio-wireshark-example icon gnuradio-wireshark-example

Simple example to show how to capture ZigBee/IEEE 802.15.4 and send it to WIreShark wpan using RFtap under GnuRadio

goertzel-fft icon goertzel-fft

A benchmark for Goertzel algorithm and `scipy.fftpack.fft` (with custom implementation of Goertzel algorithm in short-time version) **for evaluating a few DFT terms**

gopro-py-api icon gopro-py-api

Unofficial GoPro API Library for Python - connect to GoPro via WiFi.

gtsam icon gtsam

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

gyroflow icon gyroflow

Video stabilization using gyroscope data

himuserver icon himuserver

HIMUServer is a server-side solution for the app HyperIMU

i2cdevlib icon i2cdevlib

I2C device library collection for AVR/Arduino or other C++-based MCUs

imucal icon imucal

A Python library to calibrate 6 DOF IMUs

imusim icon imusim

IMUSim - see http://www.imusim.org/

instrumentino icon instrumentino

Instrumentino is an open-source modular graphical user interface framework for controlling Arduino based experimental instruments

iobb icon iobb

BeagleBone Black Interface Library (GPIO and more) for C Programmers

kalman-and-bayesian-filters-in-python icon kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

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