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Releases: CorniiDog/WhoopLib

Official First Release

01 Aug 05:08
@CorniiDog CorniiDog
v1.0.4
fa00d0c
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Latest 
v1.0.4

updated to be more consistent
Assets 2
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Added plenty of new things

11 Aug 05:26
@CorniiDog CorniiDog
v1.0.3
74077b5
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Added plenty of new things
  • Slew rate improvements
  • Bug fixes
  • Autonomous selector
  • kR "Retracted Integral" constant

Full Changelog: v1.0.1...v1.0.3

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Slight Improvements

29 Jul 12:52
@CorniiDog CorniiDog
v1.0.1
b83356a
This commit was created on GitHub.com and signed with GitHub’s verified signature.
GPG key ID: B5690EEEBB952194
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Learn about vigilant mode.
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Slight Improvements

Changed

  • x.x_v changed to x.x_volts literals
  • Added literal x_points
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WhoopLib First Release

29 Jul 08:09
@CorniiDog CorniiDog
v1.0.0
bc27726
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WhoopLib First Release

Features

  • Visual Odometry/Pose Estimation
  • Wheel Odometry/Pose Estimation, inspired by JAR-Template
  • Communication between V5 Brain and Jetson Nano
  • Fusion Odometry between Visual Odometry and Wheel Odometry
  • Rolling Average Filter for Fusion Odometry
  • WhoopController Class with auto-configuration for Split Arcade, Tank, Left Stick Arcade, and Right Stick Arcade
  • Dubins-Curves Path Creation, thanks to Andrew Walker
  • Pure Pursuit Algorithm
  • Moving between Point A and Point B
  • General PID, modified from JAR-Template
  • Turning by degrees, Turning to degrees, Turning to Face x and y Coordinates
  • Moving Forward and Reverse Functions, alongside Remembering Previous Movement Positions for Improved Resilience
  • Generated Paths with Waypoints to Navigate around the VEX Robotics Field in One Fell Swoop
  • Well-Rounded and Continuously Updated Documentation for a Low Floor yet High Ceiling
  • Slew for Motor Movements
  • Motor Voltage to Speed Linearization
  • TwoDPose Class which Handles and Simplifies Linear Algebra Mathematics, Following Similarities to Roblox's CFrames for Ease of Use

Roadmap

  • Object Detection and Gridded Permanence system
  • Detecting other robots that impede the path of the robot, and drive around
  • Implementation of a Jetson Orion Nano instead of the End-Of-Line (EOL) Jetson Nano
  • Implementation of a better SLAM solution instead of relying on the EOL Realsense T265 Camera
  • Capability to Use Different Devices like Oak-D, etc. for Visual Odometry
  • Capability to Use Lidar
  • Virtual Highway system

Acknowledgements

License

Distributed under the MIT License.

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