GRASP 2025 - Programming Robotic Arms

#robotics #kinematics #programming #ieeedekut #control-systems #computer-vision #embedded-programming #ras
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GRASP 2025

This workshop is your first step towards mastering the design, building, and programming of intelligent robotic arms, leading up to the GRASP 2025 competition. You'll learn about 4-DOF robotic arms, mechanical grippers, 3D CAD design, and control systems using Arduino Nano and Raspberry Pi. Discover how computer vision and inverse kinematics are used to achieve precise manipulation.


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  • P.O. Box 657-10100, NYERI-KENYA
  • Nyeri, Central
  • Kenya 657-10100
  • Building: DeKUT School of Engineering
  • Room Number: 2nd Floor; Dome next to Siemens Center
  • Contact Event Hosts
  • Starts 16 November 2025 05:00 PM UTC
  • Ends 01 December 2025 05:02 PM UTC
  • No Admission Charge




Agenda

1. Apply Robotic Kinematics

  • Develop a mathematical model for the robotic arm's movement using inverse kinematics.

  • Implement and test various control schemes for precise arm manipulation.

  • Analyze and compare the applications of inverse and forward kinematics.

2. Execute Embedded Programming

  • Establish serial communication protocols for hardware interfacing.

  • Program the robotic arm's functions using C++.

  • Implement precise servo motor control for all joints.

3. Develop with Computer-Aided Design (CAD)

  • Create initial design sketches and concepts for the robotic arm.

  • Determine the appropriate sizing and tolerances for links and joints.

  • Produce a complete 3D model of the robotic arm using CAD software.

  • Perform simulations within the CAD environment to test for functionality and stress.

  • Apply best practices for designing components for manufacturability.

4. Utilize 3D Printing for Prototyping

  • Prepare and slice 3D models for printing.

  • Configure and operate a 3D printer for optimal results.

  • Diagnose and troubleshoot common 3D printing issues.

5. Implement Artificial Intelligence and Computer Vision

  • Develop Python scripts for computer vision tasks.

  • Translate mathematical equations for image processing into functional code.

  • Interface vision systems with hardware components via serial communication.

  • Utilize the OpenCV library to process and analyze image data.

  • Implement and fine-tune a YOLO (You Only Look Once) model for object detection.


Creativity in Robotics