Introduction to the demos

MOV.AI Flow™ provides four demos of its ready-made functionality. The four MOV.AI Flows presented here operate in a warehouse environment. Each flow builds upon the options presented in the previous one in order to demonstrate how a complete implementation can be created on a Tugbot or a Husky robot, or any robot of your choice.

Each is provided pre-integrated and with a ready-made simulation in Gazebo Fortress and some are also provided with visualizations in RViz.

As we take you through a guided tour of four demos, we hope to impress you with the wide variety of ready-made MOV.AI flows, nodes, callbacks, code development tools, simulations, development options and labor-saving features that ROS developers can leverage to significantly expedite ROS development processes. MOV.AI Flow™ is a robot flow design tool that operates in a standard browser on a standard laptop.

  1. Simple Robot Navigation – This lesson demonstrates MOV.AI’s simple robot navigation flow using robot odometry feedback. This demo shows how easy it is to use MOV.AI Flow™ to control any robot. It demonstrates the navigation of a Husky robot and a Tugbot robot in a square pattern of 2 m x 2 m in a transparently integrated provided simulation in the Depot world of Ignition Gazebo.

  2. Mapping – This lesson demonstrates the MOV.AI mapping flow and how it can be used for any robot that requires global localization functionality. This lesson shows you how a MOV.AI flow enables a Tugbot or a Husky robot to map the environment in which it will be operating by traveling around the entire area in order to localize itself in its environment.

  3. Autonomous Navigation – This lesson demonstrates how MOV.AI’s autonomous navigation flow enables a robot to know where it is on the map, know the destination to which it has to travel (goal) and autonomously determine the path to reach that point, as well as to handle dynamic obstacles (such as people walking by) along the way.

  4. Pick and Drop – This lesson demonstrates a real-life pick and drops working MOV.AI Flow. It takes place in a similar warehouse as described in the previous lessons, except that this warehouse has been divided up into various areas – a pickup zone, a drop-off zone and a charging zone. A Gazebo Fortress map and an RViz map are provided in which you can see the robot leaving the charging station, traveling to the pickup station, picking up the cart, traveling to the drop-off station, leaving the cart there and then going back to its charging station.

Each demonstration presented in this guide describes how to play (run) it in the simulated environment provided by MOV.AI, as well as to open each flow and view/modify its definitions. You can actually perform the procedures shown in this guide as you read. You can also use the flows provided here as the basis for your own project or change them to suit any robot that you are developing in the virtual or the real world.