Home - arieldo/MorBot GitHub Wiki

Welcome to the MorBot Wiki! Here you can find everything you need to get up and running with MorBot.

To get started with MorBot, simply follow the step-by-step instructions in this wiki .

Once assembled,The educational content and docs can be accessed through the MorBot wiki or repo , which includes a range of demos and challenges that are designed to help Pupils learn about STEM and robotics concepts.

If you run into any issues, please let us know

Happy MorBotting :)

Getting started

Follow these steps and you should be up and running with MorBot in no time!

  1. Build the MorBot: - Follow the instructions in the Assemble MorBot wiki to build the robot.
  2. Set up the Jetson Nano: - Follow the instructions in the Jetson Nano And Linux wiki to set up the Jetson Nano and Linux.
  3. Install ROS: - Follow the instructions in the MorBot ROS wiki to install ROS.

MorBot package

A collection of customized ROS (Robot Operating System) packages designed to enhance robotics applications with advanced computer vision and deep learning capabilities. Each package within the MorBot suite leverages NVIDIA's powerful Jetson platform, package included in the MorBot offerings:

  • Jetbot-Camera-ROS: ROS node that interfaces with the camera on NVIDIA's JetBot.
  • Detectnet-ROS: utilizes object detection algorithms with SSD MobileNet V2 .
  • Posenet-ROS: integrates the capabilities of the PoseNet model, a body pose estimation algorithm .
  • Segnet-ROS: employs the SegNet deep learning model for pixel level semantic segmentation .

Install and run the MorBot package: - Follow the instructions in the MorBot packages to install the MorBot package.

MorBot Workshop

The ROS Workshop is a hands-on training session focused on JetBot Motion Libraries and scenario folder concept, building the cornerstone for MorBot Cool Demos part.

Follow the instructions in Ros-Workshop to Build your first Moving MorBot robot.

MorBot Cool Demos

Build engaging AI-inspired demo projects using NVIDIA Jetson and ROS. These demos are designed to showcase the integration of deep learning models and robotic control to create interactive and intelligent behaviors in small-scale robots. Below are some of the exciting projects we'll develop:

The AI Driver demo involves building AI driver scenarios for the JetBot. This project uses ROS, DetectNet for object detection, and motion control. program the JetBot to navigate autonomously, detect obstacles, make real-time driving decisions and Follow the Leader (FTL) demo enables the Jetbot to track and follow a specific object (like a person).

Look Me In The Eyes is a fascinating scenario where the goal is to have your JetBot maintain its orientation to face you directly, regardless of where you move. This is accomplished using PoseNet to identify facial keypoints. The JetBot adjusts its direction based on these keypoints to continuously face the user.

The Floor Is NOT Lava is an innovative scenario where the JetBot is required to navigate an environment by detecting and driving on the floor, using the capabilities of the SegNet deep learning model. This scenario inverts the classic children's game "The Floor Is Lava" by compelling the robot to stay on the floor rather than avoid it.

Follow the instructions in MorBot Cool Demos to Build your first MorBot Demo.