Warehouse Inspection with an Autonomous Micro Air Vehicle

Abstract

In this work, we present an approach to address the problem of warehouse inspection using a MicroAir Vehicle (MAV) that performs autonomous flight by following a set of waypoints in a GPS-denied environment. During the navigation, a second onboard camera is used to observe the inspection area where it is expected to observe QR codes attached to packages placed on shelves. To this end, we use a metric monocular simultaneous localization And Mapping (SLAM) system to estimate the MAVs position in metres, avoiding the need for an external positioning system. The onboard computer executes the detection and decoding of QR codes and the SLAM system. The MAV can also communicate with a Ground Control Station (GCS) to display telemetry, the MAVs position, images from the inspection camera with detected QR codes, and a list of the found packages. This approach was used to compete in the indoors competition of the International Micro Air Vehicle Competition (IMAV) 2019, where we received the special award: Best Flight Performance.