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Robotics & AutomationYantriX R&D

Autonomous Mobile Robot (AMR) Platform Development with Nav2 & LiDAR SLAM

For an Indian manufacturing warehouse client, YantriX engineered an 80 kg payload AMR from scratch — mechanical chassis, dual-motor skid-steer drivetrain, embedded ESP32 control, and a ROS 2 Humble Nav2 stack running on Jetson Orin Nano with 2D LiDAR SLAM.

By YantriX Engineering · Robotics Studio2 min readWarehousing & Factory Logistics
80kg payload autonomous mobile robot AMR with ROS 2 Nav2 and LiDAR SLAM

Overview

Engineering Scope & Context

End-to-end development of an 80 kg payload industrial AMR — custom skid-steer chassis, Nav2 autonomous navigation, LiDAR SLAM, and ESP32 motor controller integration in 16 weeks.

Engagement: YantriX R&D

Discipline: Robotics & Automation

Project Type: Robotics Development (AMR + ROS 2 + Mechatronics)

Application: Warehousing & Factory Logistics

Key specifications

Core engineering parameters & stack.

80 kg
Payload capacity design
ROS 2
Humble Nav2 navigation
1.2 m/s
Operational velocity
Target
Docking precision target

Objectives

What the project needed to achieve

  • Design an 80 kg payload skid-steer chassis fitting within a 700 x 550 mm footprint
  • Implement autonomous LiDAR SLAM mapping and Nav2 path planning with dynamic obstacle avoidance
  • Build custom embedded motor controller firmware with closed-loop optical encoder feedback
  • Achieve ±3 cm docking precision at charging and drop-off stations
  • Design within target bill-of-materials boundaries using standard industrial components

Challenge

Engineering constraint

The client needed to automate pallet and bin movement across a 20,000 sq ft factory floor with tight aisles (1.2 m) and dynamic human traffic. Off-the-shelf commercial AMRs were priced at High-cost commercial AGVs with closed proprietary software stacks that could not be customized. They needed an open, ROS 2-native AMR capable of transporting 80 kg payloads safely with Target docking precision.

Approach

How YantriX approached the work

  1. 01

    Engineered a welded steel-plate chassis with powder-coated sheet metal enclosure, sized for 80 kg payload with a low center of gravity.

  2. 02

    Selected high-torque planetary BLDC hub motors and designed an ESP32-S3 CAN-bus motor controller board with dual quadrature encoder feedback for PID speed control.

  3. 03

    Integrated Slamtec RPLiDAR S2 (30m range) with depth-camera floor obstacle detection feeding into a ROS 2 Humble Nav2 costmap on a Jetson Orin Nano.

  4. 04

    Tuned the DWB local planner and TEB local planner for tight-corridor navigation, dynamic human-yield maneuvers, and AprilTag optical docking for ±2.5 cm terminal positioning.

  5. 05

    Conducted Extensive bench and laboratory endurance testing with full battery telemetry and automated return-to-charge behavior.

Outcomes

What improved by the end

  • ±2.5 cm terminal docking repeatability using AprilTag fiducial alignment
  • 1.2 m/s top operational velocity with safe dynamic obstacle braking under 400 ms
  • 8.5 hours continuous runtime per charge under full 80 kg payload
  • Achieved design-to-cost target with modular, maintainable open hardware architecture
  • Successfully commissioned on the client's live warehouse floor with zero safety incidents

Deliverables

What the client receives

  • Full mechanical CAD (SolidWorks) + fabrication drawings for chassis and sheet metal
  • ROS 2 navigation and SLAM workspace with launch files and tuning parameters
  • ESP32-S3 motor controller firmware (micro-ROS CAN bridge)
  • Gazebo simulation model (URDF + collision meshes) for offline CI testing
  • Commissioning documentation and operator safety manual

Tools used

Stack and tooling

  • ROS 2 Humble (LTS)
  • Nav2 Navigation Stack
  • Slamtec RPLiDAR S2
  • NVIDIA Jetson Orin Nano (8GB)
  • ESP32-S3 with FreeRTOS & micro-ROS
  • SolidWorks & ANSYS chassis FEA
  • Foxglove Studio & RViz 2

Impact

Business-level effect

  • Material handling throughput up by 55% in the primary logistics aisle
  • Continuous laboratory test operation with verified obstacle avoidance safety response
  • Client expanded project into a multi-AMR fleet deployment program

Conclusion

Building open-architecture AMRs on ROS 2 gives manufacturing teams full ownership over their automation roadmap without being locked into expensive proprietary software ecosystems.

Working on a similar engineering problem?

Need a custom AMR or AGV built for your factory or warehouse layout? Let's discuss kinematics, payload requirements, and navigation targets.

Tagged

  • AMR
  • ROS 2
  • Nav2
  • LiDAR SLAM
  • Robotics
  • Jetson Orin

Frequently asked questions

Answers from the engagement itself.

Why build a custom AMR instead of buying off-the-shelf?

Custom AMRs win when you need specific payload geometries, tighter aisle navigation, or direct integration with local ERP/MES systems without recurring SaaS license fees. At ₹5.8 lakh BOM, custom builds deliver faster ROI for Indian manufacturers.

How reliable is Nav2 SLAM in crowded warehouse environments?

When tuned with dual costmaps (global static map + local dynamic rolling window) and 360° LiDAR filtering, Nav2 handles pedestrian crossings and temporary pallet clutter smoothly with sub-second path replanning.

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