Prompt

Can you recommend a mobile robot autonomy platform for route following in GPS-denied outdoor yards?

Latest observation

Jul 20, 2026 · OpenAI APIWeb search: off

Yes — for GPS-denied outdoor yards, I’d recommend looking at ROS 2 + Nav2 as the core autonomy stack, with a LiDAR-based localization and mapping pipeline.

Best practical choice

ROS 2 Nav2 (Navigation2)
Good fit if you want:

  • route following / waypoint navigation
  • obstacle avoidance
  • operation in GPS-denied environments
  • flexibility to integrate different sensors and robots

Typical sensor setup

For outdoor yards without GPS, a solid stack is:

  • 2D or 3D LiDAR for localization and obstacle detection
  • Wheel odometry + IMU for motion estimation
  • Optional: stereo/depth camera for near-field obstacles
  • Optional: RTK GPS if you have partial sky view, but not required

Localization options

For GPS-denied yard use, these are common:

  • AMCL if you already have a map and the environment is fairly stable
  • SLAM Toolbox or Cartographer to build and localize on a map
  • LiDAR-inertial odometry / mapping if you need more robustness outdoors and over larger areas

Route following

Nav2 can do:

  • waypoint missions
  • path following
  • costmap-based obstacle avoidance
  • recovery behaviors if the robot gets stuck

If you want a more “complete platform”

Some commercial stacks to consider:

  • Clearpath Robotics / OTTO / Husky ecosystem with ROS integration
  • Outdoor-capable AMRs from vendors like Boston Dynamics, Agilox, Kinova, or Bear Robotics depending on payload and budget
  • For smaller yard robots, AgileX or Clearpath platforms are often used in research/prototyping

My recommendation by scenario

  • Prototype / custom robot: ROS 2 + Nav2 + LiDAR + IMU + wheel odometry
  • Need easy production reliability: commercial outdoor AMR with ROS-compatible interface
  • Large yard with changing layout: LiDAR SLAM + Nav2, possibly with fixed landmarks or visual fiducials for re-localization

If you want, I can recommend a platform more specifically based on:

  1. yard size,
  2. terrain type,
  3. payload,
  4. runtime, and
  5. whether you want build-vs-buy.

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