Print Email Facebook Twitter Distance and velocity estimation using optical flow from a monocular camera Title Distance and velocity estimation using optical flow from a monocular camera Author Ho, H.W. (TU Delft Control & Simulation; Universiti Sains Malaysia) de Croon, G.C.H.E. (TU Delft Control & Simulation) Chu, Q. P. (TU Delft Control & Simulation) Date 2017-09-01 Abstract Monocular vision is increasingly used in micro air vehicles for navigation. In particular, optical flow, inspired by flying insects, is used to perceive vehicle movement with respect to the surroundings or sense changes in the environment. However, optical flow does not directly provide us the distance to an object or velocity, but the ratio of them. Thus, using optical flow in control involves nonlinearity problems which add complexity to the controller. To deal with that, we propose an algorithm that estimates distance and velocity of the vehicle based on optical flow measured from a monocular camera and the knowledge of control inputs. This algorithm applies an extended Kalman filter to state estimation and uses the estimates for landing control. We implement and test our algorithm in computer simulation and on board a Parrot AR.Drone 2.0 to demonstrate its feasibility for micro air vehicles landings. Results of the simulation and multiple flight tests show that the algorithm is able to estimate height and velocity of the micro air vehicles accurately, and achieves smooth landings with these estimates, even in windy outdoor environments. Subject autonomous landingDistance estimationefference copymonocular visionoptical flow To reference this document use: http://resolver.tudelft.nl/uuid:a0abc18b-3ee0-4b4e-aac9-c3907a07dd49 DOI https://doi.org/10.1177/1756829317695566 ISSN 1756-8293 Source International Journal of Micro Air Vehicles, 9 (3), 198-208 Part of collection Institutional Repository Document type journal article Rights © 2017 H.W. Ho, G.C.H.E. de Croon, Q. P. Chu Files PDF 1756829317695566.pdf 822.67 KB Close viewer /islandora/object/uuid:a0abc18b-3ee0-4b4e-aac9-c3907a07dd49/datastream/OBJ/view