In this paper, we propose a visual-inertial state estimation framework which is able to detect and mitigate failure modes to ensure best possible state estimation for platform control at all times. The main focus here is on the proposed sensor switching method which allows seamless switching between integration of pure inertial cues, the use of inertial-optical ow based velocity estimates, and the use of visual-inertial based position estimates for the control of an inherently unstable aerial vehicle. The switching mechanism automatically detects if a state estimator part is faulty and reduces the sensory input to the remaining, healthy, information streams. In addition, a re-initialization sequence is run for the faulty segment until the full system is recovered. With the additional capability of each segment for self-calibration, the system is both self-calibrating and self-healing. The full framework has been integrated on an embedded platform on-board a real 500g small aerial vehicle and run at 30Hz camera stream and 1kHz inertial readings for live demonstration.

Date Published: 25 May 2016
PDF: 8 pages
Proc. SPIE 9836, Micro- and Nanotechnology Sensors, Systems, and Applications VIII, 98361U (25 May 2016); doi: 10.1117/12.2225608

Published in SPIE Proceedings Vol. 9836:
Micro- and Nanotechnology Sensors, Systems, and Applications VIII
Thomas George; Achyut K. Dutta; M. Saif Islam, Editor(s)