Autonomous navigation in a warehouse with a cognitive micro aerial vehicle

Abstract

Micro aerial vehicles (MAVs), such as multirotors, are envisioned for autonomous inventory-taking in large warehouses. Fully autonomous operation of MAVs in such complex 3D environments requires real-time state estimation, obstacle detection, mapping, and navigation planning. To this end, we employ a cognitive MAV equipped with multiple sensors including a dual 3D laser scanner, three stereo camera pairs, an IMU, an RFID reader, and a powerful onboard computer running the ROS middleware. Tasks with hard real-time requirements such as attitude control and state estimation are processed on a Pixhawk Autopilot, which communicates with the main computer via the MAVLink protocol. In this chapter, we describe our integrated system for autonomous MAV-based inventory in warehouses. We detail the involved components and evaluate our system with the real autonomous MAV in a realistic scenario. We also report lessons learned during field testing.