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16.Integration system

Assignment

 -Design and document the system integration for your final project

System Integration — Delivery Robot

Overview

My final project is an Autonomous Delivery Robot for indoor environments such as offices, campuses, or hotels.

Chassis Overview

The system integrates:

Mechanical System

  • Custom-designed robot platform with hoverboard motors

  • Battery pack from hoverboard + DC–DC converter (15V → 5V)

Drive System

  • Two hoverboard BLDC motors

  • Original hoverboard control board (STM32-based)

  • ESP32 sends commands to the hoverboard board via UART protocol

Main Control System

  • Custom ESP32 PCB designed and milled by me

  • Creates Wi-Fi Access Point

  • Hosts a web interface for robot control

  • Receives HTTP commands

  • Sends movement commands to hoverboard board via UART

Network System

  • ESP32 in AP mode (“HoverESP32”)

  • Any device (laptop/phone/Raspberry Pi) can connect

  • Real-time robot control via browser buttons

  • Fully wireless communication

Sensors & Future Integration

  • IR distance sensors for collision detection (E18-D80NK)

  • Servo connector for robot lid mechanism

  • Additional pins reserved for more sensors

  • Antenna added for stable Wi-Fi range

Future Upgrade Path

  • Jetson Nano as the main onboard computer

  • SLAM system using YDLIDAR X3 Pro

  • ROS 2 navigation stack

  • Autonomous indoor navigation

  • Camera-based perception & Computer Vision

Design Process

Conceptual Design

  • Research of existing delivery robots.
  • Analysis of delivery scenarios and requirements.
  • Form factor and weight estimation.
  • Initial sketches and CAD design in Fusion.

Inventor Design

Preliminary Design

  • Platform shape and wheel positioning.
  • Motor mounting testing.
  • Driver and power system evaluation.

Detailed Design

  • 3D Printing: Full body printed on Bambu Lab X1 Carbon 24/7 over 4 days.

3D Printing in progress

VIDEO

  • CNC Wood Cutting: Platform cut from plywood with motor windows.

Cut platform

  • Electronics fixed inside the chassis.
  • Standard connectors used for modular wiring

Documentation

  • CAD files (Fusion).
  • Wiring schematics.

Packaging & Mechanical Integration

For my final project, I integrated all mechanical, electronic, and software parts of my delivery robot into one complete system.

Electronic Integration

I used my custom ESP32 control board as the main controller. The board is powered through a 5V buck converter connected to the hoverboard battery (15V). UART wires from the ESP32 go directly to the hoverboard motor driver board. All connections use JST headers, heat-shrink protection, and organized cable routing inside the robot.

Mechanical Integration

All components (battery, hoverboard board, ESP32 board, sensors, buck converter) have dedicated positions inside the 3D-printed chassis. I used screws and brackets to mount each module firmly to reduce vibration.

Sensor + Motor System

IR obstacle sensors connect to my PCB using digital pins. The hoverboard BLDC motors are controlled through UART commands sent from ESP32.

Video test bldc motor

Anticipated Failure Modes & Mitigations

Mechanical

  • Fasteners loosening — solved by lock washers and thread lockers.
  • Overload risk on platform.

Wiring

  • Strain relief implemented on all connectors.
  • Protective tubing for all wires.

Power

  • Li-Ion battery with protection circuit.
  • Over-voltage protection.

Repairability & Lifecycle

  • Modular construction.
  • Quick access to motors and electronics.
  • Upgrade-ready for ROS 2 and autonomous navigation.

Summary of Build Process

  1. Mechanical platform and chassis design (Fusion).
  2. Manufacturing (3D printing + CNC cutting).
  3. Electronics integration.
  4. Software development (ROS2 + ESP32).
  5. Testing and improvements.

First test robot

Upgrade: Jetson Nano and ROS 2 Integration

At the current stage, the robot is controlled locally.
For the next phase of development, I am upgrading the system by integrating Jetson Nano and ROS 2 to enable full autonomous navigation using SLAM and LiDAR.

This will allow the robot to: - Build its own maps. - Navigate from point A to point B autonomously. - Use computer vision and LiDAR data for obstacle detection and environment awareness.

Jetson Nano integration

This image shows the Jetson Nano Developer Kit, which will be installed on the robot.
The Raspberry Pi 4 will handle user interface and local server, while Jetson Nano will process SLAM, navigation stack, and object recognition under ROS 2.

Next integration steps:

  1. Install ROS 2 on Jetson Nano.
  2. Integrate LiDAR (YDLIDAR X3 Pro).
  3. Set up SLAM using ROS 2 Navigation Stack.
  4. Test autonomous delivery missions in a controlled environment.