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Aggressive Quadrotors Conquer Gaps With Ultimate Autonomy

IEEE Spectrum Robotics

Just a few weeks ago, we posted about some incredible research from Vijay Kumar's lab at the University of Pennsylvania getting quadrotors to zip through narrow gaps using only onboard localization. This is a big deal, because it means that drones are getting closer to being able to aggressively avoid obstacles without depending on external localization systems. The one little asterisk to this research was that the quadrotors were provided the location and orientation of the gap in advance, rather than having to figure it out for themselves. Yesterday, Davide Falanga, Elias Mueggler, Matthias Faessler, and Professor Davide Scaramuzza, who leads the Robotics and Perception Group at the University of Zurich, shared some research that they've just submitted to ICRA 2017. It's the same kind of aggressive quadrotor maneuvering, except absolutely everything is done on board, including obstacle perception.


This drone can play dodgeball – and win

Robohub

Drones can do many things, but avoiding obstacles is not their strongest suit yet – especially when they move quickly. Although many flying robots are equipped with cameras that can detect obstacles, it typically takes from 20 to 40 milliseconds for the drone to process the image and react. It may seem quick, but it is not enough to avoid a bird or another drone, or even a static obstacle when the drone itself is flying at high speed. This can be a problem when drones are used in unpredictable environments, or when there are many of them flying in the same area. Reaction of a few milliseconds In order to solve this problem, researchers at the University of Zurich have equipped a quadcopter (a drone with four propellers) with special cameras and algorithms that reduced its reaction time down to a few milliseconds – enough to avoid a ball thrown at it from a short distance.


Autonomous high flying drones learn to navigate by watching traffic below

ZDNet

Drones could be a threat to pets and powerlines, so Google has come up with a new robot to help. In countries where commercial drone delivery is permitted beyond line-of-sight (hint: not the US), autonomous drones still have a big blind spot: Urban areas. Due to interference from tall buildings, navigating city streets is all but impossible with GPS alone. Researchers at the University of Zurich and the National Centre of Competence in Research (NCCR Robotics) set out to tackle that problem. Design an algorithm that allows drones to autonomously navigate by mimicking the very traffic that delivery drones were invented to avoid.


UZH - Drohnen lernen von Autos und Velos das autonome Navigieren

@machinelearnbot

All today's commercial drones use GPS, which works fine above building roofs and in high altitudes. But what, when the drones have to navigate autonomously at low altitude among tall buildings or in the dense, unstructured city streets with cars, cyclists or pedestrians suddenly crossing their way? Until now, commercial drones are not able to quickly react to such unforeseen events.


An autonomous daredevil pushes the limits of flight

ZDNet

How do you test your mettle if you're a fighter pilot? You pull some gnarly acrobatics that push your hardware (and body) to the limit, such as the Matty flip or the power loop. Aerospace engineers have long relied on test pilots to push the limits of manned aircraft in order to learn crucial lessons about aerodynamics, thrust, and the complicated materials science behind modern planes. Drones, especially those designed for difficult environments or severe weather conditions, could benefit from the same kind of acrobatic proofing. To that end, researchers from the University of Zurich (part of the NCCR Robotics consortium) and Intel have developed a quadcopter that can perform incredible aerial acrobatics autonomously.