Optic-Flow Based Control of a 46g Quadrotor

By Adrien Briod, Jean-Christophe Zufferey, Dario Floreano. 2013

48 citations recorded by the source corpus.

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Citations in the corpus

A 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones (2018, methodology): “In [22], an optical-ﬂow-based guidance system was developed for a 46 g nano-size UAV.”
Aerodynamics and Control of Quadrotors (2017, background): “Similar to the other types of observers, velocity and position filters are usually extended Kalman filter (EKF) based Briod et al. [2013]; Grzonka et al. [2012] though some authors have proposed the use of complementary filters Sa and Corke [2012a], Cheviron et al. [2007]. These observers usually co”
Extending the Lifetime of Nano-Blimps via Dynamic Motor Control (2018, unknown): “Even for nUAVs, which typically weigh ∼ 50 g, around 5W of power are needed for the mechanical system [7].”
Target following on nano-scale Unmanned Aerial Vehicles (2017, methodology): “limitations of such MCU-based UAVs is presented by Briod et ale [6], who show an ego-motion estimation algorithm for”
Local histogram matching for efficient optical flow computation applied to velocity estimation on pocket drones (2016, background): “produced on-board processing results, however they use multiple optical flow sensors which can only detect one direction of movement [11].”
Efficient Optical Flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone (2016, background): “It is the most energy efficient and versatile sensing option, as multiple variables can be observed from the image stream: obstacles, motion, object recognition and more.”
Ultra low-power visual odometry for nano-scale unmanned aerial vehicles (2017, background): “With this results not only we are guaranteeing the given real-time constraint of 30 FPS, but we are also ensuring there is sufficient room to allocate additional computational power to other typical functionalities required by autonomous UAVs.”