Researchers at the University of Zurich, the Università della Svizzera italiana, and the University of Applied Sciences and Arts of Southern Switzerland have developed software enabling drones to autonomously detect and follow forest paths. With the new drones, missing persons can be found and rescued quickly in forests and mountain areas.
Every year, thousands of people lose their way in forests and mountain areas. In Switzerland alone, emergency centers respond to around 1,000 calls annually from injured and lost hikers. But drones can effectively complement the work of rescue services teams. Because they are inexpensive and can be rapidly deployed in large numbers, they substantially reduce the response time and the risk of injury to missing persons and rescue teams alike.
A group of researchers from the Dalle Molle Institute for Artificial Intelligence and the University of Zurich has developed artificial intelligence software to teach a small quadrocopter to autonomously recognize and follow forest trails. A premiere in the fields of artificial intelligence and robotics, this success means drones could soon be used in parallel with rescue teams to accelerate the search for people lost in the wild.
Breakthrough: Drone Flies Autonomously in Demanding Terrain
“While drones flying at high altitudes are already being used commercially, drones cannot yet fly autonomously in complex environments, such as dense forests. In these environments, any little error may result in a crash, and robots need a powerful brain in order to make sense of the complex world around them,” says Prof. Davide Scaramuzza from the University of Zurich.
The drone used by the Swiss researchers observes the environment through a pair of small cameras, similar to those used in smartphones. Instead of relying on sophisticated sensors, their drone uses very powerful artificial-intelligence algorithms to interpret the images to recognize man-made trails. If a trail is visible, the software steers the drone in the corresponding direction. “Interpreting an image taken in a complex environment such as a forest is incredibly difficult for a computer," says Dr. Alessandro Giusti from the Dalle Molle Institute for Artificial Intelligence. "Sometimes even humans struggle to find the trail!”
Successful Deep Neural Network Application
The Swiss team solved the problem using a so-called Deep Neural Network, a computer algorithm that learns to solve complex tasks from a set of “training examples,” much like a brain learns from experience. In order to gather enough data to “train” their algorithms, the team hiked several hours along different trails in the Swiss Alps and took more than 20 thousand images of trails using cameras attached to a helmet. The effort paid off: When tested on a new, previously unseen trail, the deep neural network was able to find the correct direction in 85% of cases; in comparison, humans faced with the same task guessed correctly 82% of the time.
Professor Juergen Schmidhuber, Scientific Director at the Dalle Molle Institute for Artificial Intelligence says: “Our lab has been working on deep learning in neural networks since the early 1990s. Today I am happy to find our lab’s methods not only in numerous real-world applications such as speech recognition on smartphones, but also in lightweight robots such as drones. Robotics will see an explosion of applications of deep neural networks in coming years.”
The research team warns that much work is still needed before a fully autonomous fleet will be able to swarm forests in search of missing people. Professor Luca Maria Gambardella, director of the “Dalle Molle Institute for Artificial Intelligence” in Lugano remarks: “Many technological issues must be overcome before the most ambitious applications can become a reality. But small flying robots are incredibly versatile, and the field is advancing at an unseen pace. One day robots will work side by side with human rescuers to make our lives safer." Prof. Davide Scaramuzza from the University of Zurich adds: “Now that our drones have learned to recognize and follow forest trails, we must teach them to recognize humans.”
Alessandro Giusti, Jérôme Guzzi, Dan C. Ciresan, Fang-Lin He, Juan P. Rodríguez, Flavio Fontana, Matthias Faessler, Christian Forster, Jürgen Schmidhuber, Gianni Di Caro, Davide Scaramuzza, and Luca M. Gambardella. A Machine Learning Approach to Visual Perception of Forest Trails for Mobile Robots. IEEE Robotics and Automation Letters. 9 February 2015 Doi: 10.1109/LRA.2015.2509024
Narrated video: https://youtu.be/umRdt3zGgpU
Website link: http://bit.ly/perceivingtrails
Prof. Davide Scaramuzza
University of Zurich
Director of the Robotics and Perception Group
Institute of Informatics
Phone: +41 44 635 24 09
Prof. Luca Maria Gambardella
Director of the Dalle Molle Institute for Artificial Intelligence
Phone: +41 58 666 66 63
Nathalie Huber | Universität Zürich
Stanford researchers create new special-purpose computer that may someday save us billions
21.10.2016 | Stanford University
New 3-D wiring technique brings scalable quantum computers closer to reality
19.10.2016 | University of Waterloo
Researchers from the Institute for Quantum Computing (IQC) at the University of Waterloo led the development of a new extensible wiring technique capable of controlling superconducting quantum bits, representing a significant step towards to the realization of a scalable quantum computer.
"The quantum socket is a wiring method that uses three-dimensional wires based on spring-loaded pins to address individual qubits," said Jeremy Béjanin, a PhD...
In a paper in Scientific Reports, a research team at Worcester Polytechnic Institute describes a novel light-activated phenomenon that could become the basis for applications as diverse as microscopic robotic grippers and more efficient solar cells.
A research team at Worcester Polytechnic Institute (WPI) has developed a revolutionary, light-activated semiconductor nanocomposite material that can be used...
By forcefully embedding two silicon atoms in a diamond matrix, Sandia researchers have demonstrated for the first time on a single chip all the components needed to create a quantum bridge to link quantum computers together.
"People have already built small quantum computers," says Sandia researcher Ryan Camacho. "Maybe the first useful one won't be a single giant quantum computer...
COMPAMED has become the leading international marketplace for suppliers of medical manufacturing. The trade fair, which takes place every November and is co-located to MEDICA in Dusseldorf, has been steadily growing over the past years and shows that medical technology remains a rapidly growing market.
In 2016, the joint pavilion by the IVAM Microtechnology Network, the Product Market “High-tech for Medical Devices”, will be located in Hall 8a again and will...
'Ferroelectric' materials can switch between different states of electrical polarization in response to an external electric field. This flexibility means they show promise for many applications, for example in electronic devices and computer memory. Current ferroelectric materials are highly valued for their thermal and chemical stability and rapid electro-mechanical responses, but creating a material that is scalable down to the tiny sizes needed for technologies like silicon-based semiconductors (Si-based CMOS) has proven challenging.
Now, Hiroshi Funakubo and co-workers at the Tokyo Institute of Technology, in collaboration with researchers across Japan, have conducted experiments to...
14.10.2016 | Event News
14.10.2016 | Event News
12.10.2016 | Event News
21.10.2016 | Health and Medicine
21.10.2016 | Information Technology
21.10.2016 | Materials Sciences