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AMR ROS2 Prototype | Hardware & Software Integration

This project is the development of an Autonomous Mobile Robot (AMR) prototype, serving as a foundational step toward mastering the systems engineering required for humanoid robotics.

Project Mentor: Prof. Sreedhar Madichetty
Student Mentor: R V S Srikasyap Sagar

🤖 System Overview

This project focuses on designing a mobile robot from the ground up, capable of carrying a maximum payload of 20kg from point A to point B autonomously. The objective is to move beyond theoretical study and gain real-world experience with ROS2, microcontrollers, and microprocessors.

🛠️ Hardware Stack

  • Actuation: 12V Planetary Gear DC Motors (x4) with encoders (72.5 N-cm, 185RPM).
  • Motor Control: BTS7960 Motor Drivers (x2) and Arduino MEGA2560.
  • Processing: Raspberry Pi 4 Model B.
  • Sensing: SLAMTEC RPLIDAR A1M8 (360° Laser Range Finder) and HC-SR04 Ultrasonic Sensors.
  • Weight Sensing: Load Cells (x4, 50kg) with HX711 24-Bit Amplifiers.
  • Power: 3S Lithium Polymer (LiPo) Battery (11.1V, 2200mAh) with LM2596S DC-DC Buck Converter.

💻 Software & Middleware

  • Operating Systems: Ubuntu 22.04 LTS and Windows 11.
  • Middleware: ROS2 Humble with Nav2 Stack and SLAM Toolbox.
  • Firmware: Arduino IDE and Micro-ROS.
  • Design Tools: Autodesk Inventor, Cirkit designer IDE, and Tinkercad.
  • Simulation: Gazebo and RViz2.

🗺️ Roadmap

Stage 1: The Hardware MVP

  • Comprehensive circuit and mechanical design.
  • Chassis fabrication, assembly, and wiring.
  • Initial system integration and low-level programming.

Stage 2: The Digital Twin

  • Spatial frame architecture and kinematic modeling.
  • Dynamic state broadcasting and parametric model optimization.
  • Physics engine integration for simulation accuracy.

Stage 3: The Brain Transplant

  • Microcomputer (Raspberry Pi) environment provisioning.
  • Serial UART bridge implementation and kinematic odometry publishing.
  • Velocity command subscription and closed-loop teleoperation validation.

Stage 4: Autonomy & Perception

  • Probabilistic SLAM and Map Generation.
  • Custom environment simulation and fine-tuning.
  • Autonomous path planning validation and hardware Nav2 integration.

📂 Repository Structure

  • /src: ROS2 packages and Python nodes for robot logic.
  • /hardware_cad: Autodesk Inventor (.ipt, .iam) models and circuit schematics.
  • .gitignore: Configured to exclude build, install, and log artifacts.

📈 Learning Goals

My primary motivation is to utilize hands-on learning to understand robotics from the ground up. By building this robot from scratch-designing hardware, wiring electronics, and writing code - I am mastering the foundational gears of autonomous systems.

🙏 Acknowledgments

Special thanks to the following individuals for their technical guidance:

About

Autonomous Mobile Robot (AMR) Prototype using ROS2 and Python. Features custom motor control nodes and mechanical architecture designed in Autodesk Inventor.

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