Lab4Geo
Domain — Robotics & Automation

Robotics and industrial automation platforms.

We build the spatial intelligence that robots and automated systems need — SLAM, calibration, perception, sensor fusion, and the software that ties them into real operations.

Discuss a Project See Example Use Cases
Robotics and industrial automation

Why robotics software is hard in the real world.

Robots work in the lab. The factory floor, the hospital corridor, and the warehouse aisle are different problems.

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The lab-to-field gap

Perception works under controlled lighting and clean inputs. Real deployments hit glare, dust, motion, and unpredictable humans.

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Calibration drift

Sensors degrade with temperature, vibration, and wear. A robot that was accurate at commissioning may not be accurate a month later.

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Integration complexity

Robots need to talk to fleet software, safety systems, and enterprise platforms — each with its own protocol and constraints.

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Edge compute limits

The algorithm has to run on the robot, not in a data centre. Power, memory, and latency budgets are tight.

Example use cases.

Where robotics and automation software delivers real operational reliability.

Robotics SLAM Healthcare & Hospitality

Indoor service robots for hospitals and hotels

The scenario: A robotics company is deploying autonomous service robots into hospitals and hotels. The robots must navigate unfamiliar indoor environments, avoid people, and stay accurate over long shifts — without on-site technicians.

How we help: We implement and tune the SLAM stack, build self-calibration routines that let the robot recover accuracy on its own, and harden the localization pipeline for real-world edge cases.

  • Production-grade SLAM pipeline (ROS 2 or custom)
  • Self-calibration and drift-correction routines
  • Sensor fusion for camera, LiDAR, IMU, wheel odometry
  • Field-testing harness and accuracy reporting
Warehouse AMR Fleet

Autonomous mobile robots for warehouses

The scenario: A warehouse automation company is deploying a fleet of AMRs into active distribution centres. Navigation, traffic coordination, and safe interaction with human pickers must all work together.

How we help: We build the fleet localization and coordination stack — map sharing, traffic scheduling, dynamic replanning, and safe handover to human operators.

  • Fleet-wide localization and map sharing
  • Traffic coordination and deadlock avoidance
  • Dynamic replanning around obstacles and humans
  • Integration with warehouse management systems
Industrial Inspection 3D Perception

Industrial inspection robots

The scenario: A manufacturer is automating inspection with a robot-mounted 3D scanner. The perception pipeline works in the lab but fails on the factory floor where lighting, dust, and vibration vary.

How we help: We harden the perception pipeline for industrial conditions, add spatial registration and defect localization, and integrate with asset management systems.

  • Robust 3D perception pipeline
  • Point cloud registration and defect localization
  • Integration with asset management systems
  • Field validation and accuracy benchmarks
Sensors Calibration Fleet

Sensor pod calibration for fleets

The scenario: A company sells a sensor pod that combines cameras, LiDAR, and IMU. Every unit ships slightly different, and customers expect it to "just work" out of the box.

How we help: We design the factory calibration procedure, build the self-calibration logic that runs at boot and in the field, and deliver the tooling for manufacturing validation.

  • Factory calibration procedure and tooling
  • On-device self-calibration routines
  • Extrinsic and intrinsic calibration pipelines
  • QA reports and pass/fail thresholds per unit

Let's discuss your robotics stack.

Tell us what you're building and where the spatial engineering is slowing you down. We'll come back with a scoped path forward.

Start the Conversation

or email me directly at darion.grant@gmail.com