project-sharwin24
project-Sharwin24 created by GitHub Classroom
Science Score: 13.0%
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○CITATION.cff file
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✓codemeta.json file
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○.zenodo.json file
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○Scientific vocabulary similarity
Low similarity (10.3%) to scientific vocabulary
Repository
project-Sharwin24 created by GitHub Classroom
Basic Info
- Host: GitHub
- Owner: NU-MECH-ENG-495
- Language: C++
- Default Branch: main
- Size: 1.81 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Project Overview
A ROS2 Package hosting a Kalman Filter from scratch to combine data from a 9-DoF IMU and a time-of-flight distance sensor attached to the end-effector of a delta robot. The filter will be used to estimate the position and velocity of the end-effector in 3D space.Results will be visualized with a 3D plot, written in C++ and compared to kinematics estimations from the robot's control system.
Learning Concepts: - Kalman Filtering - Reading I2C data from high-speed sensors - Eigen Library (C++ Library for Linear Algebra and Matrices) - Graphics and Plotting in C++
Sensor Details
BNO085 IMU
The BNO085 IMU has the following features:
- Acceleration Vector / Accelerometer
- Three axes of acceleration (gravity + linear motion) in m/s^2
- Angular Velocity Vector / Gyro
- Three axes of 'rotation speed' in rad/s
- Magnetic Field Strength Vector / Magnetometer
- Three axes of magnetic field sensing in micro Tesla (uT)
- Linear Acceleration Vector
- Three axes of linear acceleration data (acceleration minus gravity) in m/s^2
- Gravity Vector
- Three axes of gravitational acceleration (minus any movement) in m/s^2
- Absolute Orientation/ Rotation Vector
- Four point quaternion output for accurate data manipulation
Thanks to the sensor fusion and signal processing wizards from CEVA, with the BNO085 you also get:
- Application Optimized Rotation Vectors
- For AR/VR, low latency, and low power consumption
- Additional Base Sensor Reports
- Separate and simultaneous outputs of Calibrated, Uncalibrated + Correction, and Raw ADC outputs for the Accelerometer, Gyro, and Magnetometer
- Detection and Classification reports:
- Stability Detection and Classification
- Significant Motion Detector
- Tap, Step, and Shake Detectors
- Activity Classification
VL53L1X Time of Flight Distance Sensor
The VL53L1X ToF Sensor is capable of precise distance measurement within a range of $[30, 4000]$ mm, with up to a 50Hz update rate and a $27^\circ$ field of view which can be configured with a programmable Region of Interest (ROI).
Resources
- https://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf
- https://groups.seas.harvard.edu/courses/cs281/papers/unscented.pdf
- https://www.kalmanfilter.net/default.aspx
- https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
Owner
- Name: NU-MECH-ENG-495
- Login: NU-MECH-ENG-495
- Kind: organization
- Repositories: 1
- Profile: https://github.com/NU-MECH-ENG-495
Citation (citations.txt)
GitHub Events
Total
- Issue comment event: 1
- Member event: 1
- Push event: 80
- Pull request event: 7
- Create event: 5
Last Year
- Issue comment event: 1
- Member event: 1
- Push event: 80
- Pull request event: 7
- Create event: 5
Issues and Pull Requests
Last synced: 10 months ago
All Time
- Total issues: 0
- Total pull requests: 3
- Average time to close issues: N/A
- Average time to close pull requests: 3 days
- Total issue authors: 0
- Total pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.33
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 3
- Average time to close issues: N/A
- Average time to close pull requests: 3 days
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.33
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
- Sharwin24 (3)