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Client Case StudyClient work · anonymized

ROS 2 Relocalization for an Autonomous Robot-Vacuum Maker

Coverage cleaning and kidnapped-robot recovery for an open-source robot vacuum, on ROS 2.

A ROS 2 Jazzy / Nav2 milestone: a boustrophedon coverage planner and kidnapped-robot recovery, validated by headless regression suites.

What makes it serious
  • Boustrophedon coverage planner on ROS 2 Jazzy / Nav2
  • Kidnapped-robot recovery via relocalization
  • Headless Gazebo regression suites for reproducible acceptance
  • Measured: ~90% coverage, ~87% path efficiency, 10/10 relocalize at ~6s / <=0.12m

A milestone engagement for a maker of open-source autonomous robot vacuums. The work delivered two behaviours on ROS 2 Jazzy with Nav2 and Gazebo: a boustrophedon coverage planner that sweeps a room efficiently, and a kidnapped-robot recovery routine that relocalizes the robot after it is picked up and moved. Both were validated by headless regression suites so results are reproducible in CI, not just on a demo run.

The measured outcomes from the regression harness: roughly 90% area coverage, about 87% path efficiency, and 10 out of 10 successful relocalizations averaging six seconds at sub-0.12-metre accuracy. Beyond trading automation, this demonstrates real robotics and systems-engineering range: navigation stacks, simulation, and metric-driven acceptance testing. Client name withheld under the engagement. Reporting the numbers straight from the regression harness, rather than a hand-picked demo run, is what makes the milestone defensible, and the headless suites mean anyone can reproduce those figures in CI.

Stack
ROS 2 JazzyNav2AMCLGazeboPythonLinux
#ros2#robotics#nav2#gazebo#relocalization#client-work