Progress on ‘pico’ air vehicles
By Robert J. Wood, Benjamin M. Finio, Michael Karpelson, Kevin Y. Ma, Néstor Osvaldo Pérez-Arancibia, Pratheev S. Sreetharan, Hiroyuki Tanaka, John Peter Whitney. 2012
181 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Condensed Matter Physics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Antonio Loquercio
- Luca Benini
- Daniele Palossi
- Davide Scaramuzza
- Henri Rebecq
- Vladlen Koltun
- Daniel Cremers
- Guoquan Huang
Citations in the corpus
- A 64-mW DNN-Based Visual Navigation Engine for Autonomous Nano-Drones (2018, background): “Even if it were possible to linearly up-scale the performance of this microcontroller to the same level of our system, it would consume ∼ 880 mW, which would constitute largely more than the 5% of power envelope typically dedicated to onboard computation on nano-UAV systems [14].”
- Target following on nano-scale Unmanned Aerial Vehicles (2017, background): “Wood et ale [10] estimated in 5mW the power budget for on-board computation on pico-size UAVs, showing how this only accounts for 5% of the total, the rest being used by the propellers (86%) and the low-level control parts (9%).”
- 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.”