Boston Magazine reporter Kyle Clauss reports that researchers from MIT CSAIL have developed a drone that uses algorithms to detect obstacle-free regions in space. “Using free-space segments is a more ‘glass-half-full’ approach that works far better for drones in small, cluttered spaces,” says MIT alumnus Benoit Landry.
Researchers from MIT CSAIL have developed an algorithm that allows drones to navigate obstacle courses, reports Kelsey Atherton for Popular Science. “As drones move away from simple remote-controlled toys and become more autonomous flying tools, programs like these will keep them flying safely through unfamiliar terrain,” explains Atherton.
In this video, Jim Drury of Reuters examines the new system developed by MIT researchers that enables drones to map and successfully navigate a new landscape.
Washington Post reporter Matt McFarland writes about graduate student Andrew Barry’s work developing a system that allows drones to successfully navigate obstacles. McFarland writes, “the work is significant because it shows a drone avoiding obstacles in an area that hasn’t been previously mapped.”
MIT researchers have developed a detection system that allows a drone to navigate obstacles while flying at speeds of 30 mph, writes Barb Darrow for Fortune. Darrow explains that the research is aimed at mitigating “the risk of using potentially very useful technology not just for package delivery but for building or land inspections, journalism, even fire fighting.”
Graduate student Andrew Barry has created software that allows a self-piloting drone to dodge obstacles at 30 miles per hour, reports Robert Ferris for CNBC. “The software, which is open source and available for free online, runs 20 times faster than existing navigational software,” reports Ferris.
Alyssa Newcomb reports for ABC News on a system developed by graduate student Andrew Barry that allows drones to avoid obstacles. Newcomb explains that the system, "operates at 120 frames per second and is able to extract depth information at a speed of 8.3 milliseconds per frame."
MIT researchers “demonstrated that a drone can zip through a maze of trees at 30 miles per hour swerving past obstacles in its way. The craft was able to do this using a stereo-vision algorithm that rapidly detects and avoids objects immediately in front of the craft,” reports Nidhi Subbaraman for BetaBoston.
MIT researchers have developed a drone that can recognize obstacles while flying at speeds of 30 miles per hour, writes Mary Beth Griggs for Popular Science. The drone creates a map of the world, “identifying obstacles, and mapping a path around them.”
Anna Nowogrodzki reports for New Scientist on Hyrdoswarm, a company founded by graduate student Sampriti Bhattacharyya that is designing autonomous robots to map the oceans. “A network of autonomous drones could be used for disaster response, coral reef monitoring, surveillance for port security and finding places to drill for oil and gas,” writes Nowogrodzki.
Amanda Hoover writes for Boston.com about how researchers from the MIT Media Lab demonstrated a drone-based drawing system during HUBweek. “This is more about the idea of how machine and man can be integrated and work together,” says graduate student Sang-won Leigh. “What I want to do is show what kind of future is possible.”
Researchers from MIT and Olin College are developing technology that could allow fleets of drones to aid firefighters in combatting wildfires, reports Barb Darrow for Fortune. The drones would be used to “collect intelligence about the fire as fast as possible for human fire-fighting experts,” writes Darrow.
Prof. Jonathan How and his colleagues are developing a fleet of autonomous drones that could help gather information about wild fires, writes Brian Dowling for The Boston Herald. “These drones will let a firefighter select a point of a fire on a map, then send a drone there to examine the fire and report back with data,” explains Dowling.
Team Raptor Maps received the top prize in MIT’s annual $100K Entrepreneurship Competition, reports Nidhi Subbaraman for BetaBoston. Founded by three MIT students, Raptor Maps “proposes to use camera-carrying drones to survey farmland and pinpoint damage before pests and diseases can decimate crops.”
In this video, MIT researcher Chris Green speaks with BBC Click about the swarm of autonomous drones developed by the MIT SENSEable City Lab that can communicate with one another and could be used to test water quality. Green explains that the drones can be outfitted to “include all sorts of sensors… from water quality to air quality.”