Autonomous Mapping & Infrastructure Inspection
Perception, localisation, visual SLAM, 3-D reconstruction, object detection, and geospatial workflows for real-world infrastructure systems.
Learn more
- C++/ROS2 native · Edge-ready
- SLAM · perception · sensor fusion
- ACT · diffusion policy · LeRobot workflows
Production Robotics Stack
C++, ROS2, perception, planning, control, diagnostics, and edge deployment brought together for field-ready autonomous systems.
Robot Learning Workflows
Action/observation design, demonstration data, policy evaluation, imitation learning, diffusion policy, ACT, and LeRobot-style pipelines.
Real-World Integration
Sensors, actuators, backend services, logging, error handling, and deployment boundaries shaped for fast-moving engineering teams.
From Prototype to Field-Ready Robotics
A practical engineering path for turning autonomy research, perception models, and robot-learning workflows into robust systems that can be tested, debugged, and deployed.
- 1
Scope
Define robot task, sensors, action space, observation interfaces, latency budget, risks, and deployment constraints.
- 2
Build
Develop modular C++/ROS2 components for perception, localisation, planning, control, logging, and diagnostics.
- 3
Evaluate
Run simulation, regression tests, policy evaluation, trajectory review, failure analysis, and edge-case checks.
- 4
Integrate
Connect sensors, actuators, edge compute, backend services, teleoperation, data capture, and field workflows.
- 5
Deploy
Harden APIs, document handover, monitor behaviour, troubleshoot field issues, and improve production readiness.
C++ · ROS2 · PythonVisual SLAM · odometry · state estimationOpenCV · PyTorch · transformer policiesJetson/x86 edge deployment · DockerSimulation · testing · diagnostics
Frameworks & Technology We Work With
Robotics, AI & Autonomy Teams
Bring Xipotech into a difficult robotics programme where C++/ROS2 software, perception, localisation, mapping, planning, control, robot learning, and field deployment need to work together.