Software & Control
Welcome to the Software & Control (CSE) module of the RoboArm 2026 handbook. In this track, you will learn how to write low-level firmware for real-time actuator control and implement computer vision and kinematic algorithms on your PC.
Module Toolchain
Make sure your local development environments and interpreters are configured prior to our coding sessions:
Ensure you install Python 3.10+ on your system and set up a clean virtual environment (.venv) inside VS Code before installing vision libraries like OpenCV.
| Tool | Purpose | Access Link |
|---|---|---|
| Thonny IDE | Lightweight IDE for flashing firmware and running MicroPython on microcontrollers | Download Thonny ↗ |
| Visual Studio Code | Primary code editor for host PC control, trajectory planning, and algorithms | Download VS Code ↗ Python Extension for VS Code ↗ |
OpenCV (cv2) | Real-time computer vision pipeline, color tracking, and ArUco fiducial marker pose estimation | OpenCV Documentation ↗ |
Module Roadmap
Follow the sequential workshop track using the navigation sidebar on the left:
-
01. Embedded Systems & MicroPython
MicroPython basics, GPIO manipulation, PWM servo signals, and serial telemetry. -
02. Kinematics & Motion Algorithms
Forward and inverse kinematics (IK), workspace limits, interpolation, and smooth trajectory planning. -
03. Computer Vision & Autonomous Control
OpenCV image pipelines, HSV color detection, ArUco marker detection & 6-DOF pose estimation, camera calibration, and closed-loop visual servoing.
Submit your repository links or algorithm verification videos via the top navigation bar at Submissions.