David Niewinski of Dave’s Armoury won the ‘Jetson Project of the Month’ for building a robot arm capable of playing a perfect game of cornhole.
Overview
David Niewinski from Dave’s Armoury created a robotic arm that plays cornhole using the NVIDIA Jetson AGX Xavier Developer Kit. The project showcases the integration of computer vision and robotics to achieve precise gameplay.
What You'll Learn
1
How to use OpenCV functions for object detection in robotics
2
Why the NVIDIA Jetson AGX Xavier is suitable for robotics applications
3
How to calculate throwing angle and power for robotic arms
Prerequisites & Requirements
- Basic understanding of robotics and computer vision concepts
- Familiarity with NVIDIA Jetson AGX Xavier and OpenCV(optional)
Key Questions Answered
How does the robotic arm play cornhole?
The robotic arm, named Susan, uses a 1080p webcam to detect the red hole on the cornhole platform and calculates the angle and power needed for a successful throw using OpenCV functions like inRange and findContours.
What technology powers the robotic arm?
The robotic arm operates on the NVIDIA Jetson AGX Xavier Developer Kit, which combines high parallel compute capabilities suitable for running neural networks and machine vision applications without consuming much power.
What software is used for communication between Jetson and the robot?
The Jetson communicates the calculated throwing parameters to the Kuka KR20 robot using the KUKA.ethernetKRL software package, facilitating precise control over the robotic arm's movements.
Technologies & Tools
Hardware
Nvidia Jetson Agx Xavier
Used as the main computing unit for processing data and controlling the robotic arm.
Software
Opencv
Used for image processing tasks such as detecting the cornhole hole and calculating throw parameters.
Hardware
Kuka Kr20
The robotic arm that executes the throwing action based on calculations from the Jetson.
Key Actionable Insights
1Integrating computer vision with robotics can significantly enhance automation tasks.This project exemplifies how vision systems can be used to improve accuracy in tasks like throwing, which is essential in various industrial applications.
2Using the NVIDIA Jetson AGX Xavier can streamline the development of intelligent robotic systems.Its ability to handle complex computations while maintaining low power consumption makes it ideal for robotics projects.
3Utilizing OpenCV for real-time image processing can greatly improve the functionality of robotic systems.By leveraging OpenCV functions, developers can implement effective object detection and tracking, which are crucial for interactive robotics.
Common Pitfalls
1
Overlooking the importance of camera positioning can lead to inaccurate object detection.
Proper calibration and positioning of the camera are crucial for the system to correctly identify the target, which can affect the performance of the robotic arm.