delivery robot

1. Introduction to the Project and System Overview

• Project objectives and goals
• Overview of the hardware setup and connections
  • Arduino Mega with IMU, GPS, and BLDC motor
  • Jetson Nano with RPLIDAR A1M8-R6 and Intel RealSense D415
• Understanding roles of each component in a delivery robot

2. Arduino Mega Setup and Sensor Communication

• IMU Setup and Calibration
  • Understanding IMU data (orientation, acceleration)
  • Reading and calibrating IMU data using Arduino
• GPS Data Handling
  • Parsing GPS data (latitude, longitude, altitude) on Arduino
  • Converting GPS coordinates into a format usable for ROS2
• BLDC Motor Control
  • Basics of BLDC motor control and PWM signal
  • Programming Arduino to control motor speed and direction

3. ROS2 Communication with Arduino (Using ROS2 Serial Bridge)

• Introduction to ROS2-Arduino communication
• Setting up rosserial or ros2arduino for serial communication between Jetson Nano and Arduino Mega
• Publishing IMU and GPS data to ROS2 topics
• Subscribing to control commands from Jetson Nano for motor control

4. Jetson Nano Sensor Setup and Integration

• RPLIDAR A1M8-R6 Setup
  • Configuring RPLIDAR with ROS2 and verifying data in RViz
• Intel RealSense D415 Setup
  • Integrating RealSense with ROS2
  • Understanding RGB-D data and depth image processing
• Synchronizing RPLIDAR and RealSense data for SLAM and obstacle detection

5. Building a 3D Model and URDF for the Delivery Robot

• Creating a URDF model of the robot including:
  • Base Frame for Jetson Nano and Arduino
  • Mounting IMU, GPS, and BLDC Motor on the robot model
  • Adding RPLIDAR and RealSense sensor positions
• Visualizing the URDF model in RViz and testing sensor data orientation

6. Setting Up Gazebo Simulation Environment

• Configuring Gazebo with custom delivery robot model
• Adding simulated environments for testing (e.g., urban streets, obstacle courses)
• Integrating RPLIDAR and RealSense sensors into the Gazebo simulation
• Testing BLDC motor control in Gazebo with basic movement commands

7. Implementing Sensor Fusion and Localization

• Using robot_localization package to fuse IMU, GPS, and odometry data
• Configuring an EKF (Extended Kalman Filter) for accurate localization
• Testing localization accuracy in Gazebo and verifying data in RViz

8. SLAM and Mapping with RPLIDAR and RealSense

• 2D SLAM using RPLIDAR and 3D Mapping with RealSense depth data
• Setting up SLAM Toolbox or Cartographer for map generation
• Visualizing generated maps in RViz
• Testing map accuracy and refining parameters

9. Path Planning and Obstacle Avoidance

• Setting up Nav2 (Navigation Stack 2) for ROS2
• Defining global and local planners for pathfinding
• Configuring costmaps using RPLIDAR and RealSense data
• Implementing obstacle avoidance behaviors in dynamic environments

10. Autonomous Navigation and Delivery Task Simulation

• Setting delivery points (waypoints) based on GPS coordinates
• Creating a navigation goal and testing route planning
• Verifying that the robot reaches each waypoint successfully in Gazebo
• Integrating logic to return to the base station after delivery

11. Testing and Fine-tuning the Real-world Setup

• Transitioning from simulation to real-world tests
• Synchronizing real sensors with simulated parameters
• Adjusting navigation, localization, and SLAM parameters for real-world conditions
• Conducting test runs and refining performance

12. Advanced Topics and Enhancements

• Adding voice command or gesture control for enhanced interactivity
• Exploring object detection with RealSense for specific tasks
• Extending the project with multi-robot coordination or fleet management