THE FACTS<\/strong>:<\/p>\n \u201cSense and avoid\u201d for drones is a popular topic in the press right now, but the phrase can mean different things in different contexts and for different people. To clarify, there is a difference between solving the problem of \u201csense\u201d and solving the problem of \u201cavoid.\u201d \u00a0Also, there is a difference between \u201cairborne collision avoidance\u201d (which is what most concerns the FAA) and \u201cobstacle avoidance\u201d (which is the problem that most manufacturers are trying to solve right now). With that in mind, this post looks at what a few manufacturers and software providers are doing to solve obstacle avoidance.<\/p>\n WHAT\u2019S COOL AND WHAT\u2019S NOT<\/strong>:<\/p>\n DJI<\/strong> \u2013 DJI was one of the first to release a drone that could sense and avoid obstacles. In June 2015, they announced Guidance<\/a>, a combination of ultrasonic sensors and stereo cameras that allow the drone to detect objects up to 65 feet (20 meters) away and stay away from objects at a preconfigured distance. The kit was immediately available for the Matrice 100<\/a> drone development platform.\u00a0 They subsequently incorporated that technology into their flagship Phantom 4<\/a> prosumer drone but not their new professional drone, the Matrice 600<\/a>.<\/p>\n The Phantom 4 has front obstacle sensors combined with advanced computer vision and processing that allow it to react to and avoid obstacles in its path. The secret sauce for the Phantom 4\u2019s ability to sense and avoid obstacles in real time and hover in a fixed position without a GPS signal is a set of specialized software algorithms for spatial computing and 3D depth sensing. These algorithms are coupled with an onboard Movidius vision processing unit (VPU)<\/a> that gives the Phantom 4 drone the ability to sense and avoid obstacles in real time. In the \u201cTapFly Mode\u201d of the flight control program, the Phantom 4 obstacle sensing systems are supposed to enable you to fly a path with the drone automatically moving around objects as it flies. But you can find several real-world tests like this one<\/a> that show it\u2019s not a perfect system.<\/p>\n Intel <\/strong>\u2013 Intel is all over sense and avoid, and they accomplish it with active sensors. In 2015 at the Consumer Electronics Show (CES), they gave this sneak peek<\/a> at what they were working on. In January 2016, they acquired German drone manufacturer Ascending Technologies (AscTec) and dazzled CES with an on-stage demo<\/a> of their Intel\u00ae RealSense\u2122 technology<\/a> integrated into an AscTec drone that showcased how it can avoid obstacles and continue to follow the subject. They\u00a0recently announced<\/a> their Aero Ready-to-Fly Drone,\u00a0a fully functional quadcopter powered by the Intel\u00ae Aero Compute Board, equipped with Intel\u00ae RealSense\u2122 depth and vision capabilities and running an open-source Linux operating system. It is geared for developers, researchers, and UAV enthusiasts.<\/p>\n It\u2019s clear Intel understands the importance of sense and avoid technology for ready-to-fly prosumer and commercial drones, too. In June 2016, Intel announced<\/a> the addition of a factory-installed Intel RealSense R200 camera and an Intel Atom processor module for Yuneec\u2019s Typhoon H<\/a>.\u00a0 The module will map the Typhoon H’s surroundings in 3D, which it then uses to autonomously navigate its environment\u2014including rerouting itself around obstacles. Yuneec’s Typhoon H camera drone already had the ability to stop itself before colliding into large objects. But now it should avoid obstacles and keep moving right around them. We\u2019ll see if that comes true in the real world. Let\u2019s hope it does. Otherwise Intel\u2019s $60 million investment in Yuneec<\/a> may show signs of not delivering the expected return.<\/p>\n Either way, Intel has hedged its bets. In July 2016, a team from Intel and Airbus demonstrated an aircraft visual inspection with a modified AscTec Falcon 8 with RealSense cameras. The demo<\/a> took place during this week\u2019s Farnborough International Airshow in England on an Airbus passenger airliner. \u00a0Additionally, in September 2016, Intel acquired DJI\u2019s VPU vendor Movidius<\/a>, which means they may have the market cornered for sense-and-avoid technology.<\/p>\n Parrot<\/strong> \u2013 Parrot\u2019s S.L.A.M.dunk<\/a> integrates advanced software applications based on the robotic mapping construct called \u201csimultaneous localization and mapping,\u201d or SLAM<\/a>.\u00a0 The name of Parrot\u2019s solution is a play on the words “slam dunk,” but really it\u2019s anything but that.\u00a0 SLAM is a computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent’s location within it. Parrot\u2019s use of SLAM enables a drone to understand and map its surroundings in 3D and to localize itself in environments with multiple barriers and where GPS signals are not available. In other words, it performs obstacle avoidance. Their solution depends on active sensors. You can read more here<\/a>.<\/p>\n Neurala<\/strong> \u2013 Neurala<\/a> is a software solution that analyzes the images from off-the-shelf cameras to enhance drone navigation. Unlike Parrot\u2019s solution, Nueurla technology is passive. It uses GPU-based hardware running artificial intelligence neural network software. While commercial-grade GPS can fly a drone close to its objectives, Neurala software can help it identify safe areas to travel and land. At InterDrone, Neurala announced <\/a>the launch of Bots Software Development Kit. The kit will allow manufacturers to install artificial-intelligence \u201cneural\u201d software directly into their applications without the need for additional hardware. That said, full collision avoidance is still under development.<\/p>\n LeddarTech<\/strong> – Leddar just announced<\/a> its modular Vu8. The specs make it ideal for autonomous drone use. The Vu8 is a compact solid-state LiDAR sensor that detects targets at a range of up to 705 feet (or 215 meters) and weighs 75 grams. The Vu8 is an active sensor that \u201ccould be\u201d used for collision avoidance, navigation, and as an altimeter for drones. According to LeddarTech, the Vu8 LiDAR is \u201cimmune to ambient light\u201d and was designed to provide \u201chighly accurate multi-target detection over eight independent segments.\u201d There are some cool details in this video<\/a> but no real-life use on a drone demo just yet.<\/p>\n BOTTOM LINE:<\/strong><\/p>\n At this time, the drone industry appears to be rich with R&D and solutions that attempt to tackle the obstacle avoidance problem. But a simple search on YouTube for successful real-world examples reveals we still have a way to go before anyone claims victory. I like what LeddarTech says<\/a>:<\/p>\n Available drones sensing solutions for position and range measurements as well as for collision avoidance are still far from perfect: GPSs and barometers aren\u2019t full-proof\u2014even outdoors\u2014and can\u2019t be relied upon when navigating indoors. Ultrasonic altimeters have very limited range. Optical flow sensors require good lighting and textured surfaces, and camera vision are still a work in progress and tend to be processing-intensive.<\/p><\/blockquote>\n As with any technology, there are always trade-offs. It\u2019s still not clear to me who has the category-killing solution. I think that\u2019s going to take more R&D investment. One thing is for sure\u2014we\u2019ll see more new sense-and-avoid product and tech announcements this year. Like with DJI, I believe it will continue to be released first in prosumer drones because that\u2019s the only place where sales volumes and margins are strong enough to recoup the investment.<\/p>\n Image credit: Intel<\/p>\n —<\/p>\n This post first appeared on DRONELIFE.com<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"