Indoor MAV auto-retrieval using fast 6D relocalisation

This paper develops and evaluates methods for performing auto-retrieval of a MAV using fast 6D relocalisation from visual features. Auto-retrieval involves a combination of guided operation to direct the vehicle through obstacles using a human pilot and autonomous operation to navigate the vehicle on its return or during re-exploration. This approach is useful in tasks such as industrial inspection and monitoring, and in particular to operate indoors in GPS-denied environments. Our relocalisation methodology contrasts two sources of information: depth data and feature covisibility but in a novel manner that validates matches before a RANSAC procedure. The result is the ability of performing 6D relocalisation at an average of 50Hz on individual maps containing 120K features. The use of feature co-visibility reduces memory footprint as well as removes the need to employ depth data as used in previous work. This paper concludes with an example of an industrial application involving visua...

• Type: Journal
• Year: 2016
• Where: AR
• Authors: José Martínez-Carranza, Richard Bostock, Simon Willcox, Ian D. Cowling, Walterio W. Mayol-Cuevas
• Keywords: AR 2016, Software Engineering