Have you ever wondered how you can walk or jog while bouncing your head up and down while focusing on objects near or far away? Did you find a way to do the same thing to quickly and accurately determine the distance, velocity, and details of an object? Well, the reason you can do this well is the mind that helps you quickly fill in the details using frame bursts of images from your memory and retinal jitter, and how the visual cortex fills in the blanks-this is all. A few seconds using a brain that consumes very little 20 watts of power that happens in the micro. Wow, talk about cutting-edge organic design and technology-my fellow humans are impressive.
Of course, some animals and birds have much smaller brains and do this better than we do. Consider whether you will be an owl, a hawk, or a bald eagle. Think of the phrase “Eagle Eyes” as appropriate here. Biomimetic strategies can be used to make UAVs (unmanned aerial vehicles) or drone video imaging more powerful and sensitive. In doing so, think a little about the number of applications this affects. How have you been working on these concepts so far? Now, 3-axis gimbals are most sought after by small drone owners, but why 3-axis if you can create a 4, 5, or 6-axis gyro-stabilized gimbal to improve video resolution and accuracy? Do you use? So does the quadcopter design, which is very stable even in moderate eddy, as it does help stabilize the camcorder.
Let’s talk a bit about strategies to reach the eagle eye abilities found in nature. A patent, “Devices and Methods for Stabilization and Vibration Reduction,” US 9277130 B2 officially states: , Lens stabilization, sensor stabilization, and overall imaging equipment stabilization. “
If you also use a visual recognition system for frame bursts and focus only on those that meet the mission criteria, the “OR” will be completely anomalous (out of place). In the human mind, out of place causes the N400’s brain waves to arouse curiosity, nuances and interests. You can program the same using an algorithm that requires a video camera. Investigate, identify and act. Or, as Colonel Boyd’s “OODA Loop Strategy” suggests, observe, direct, decide, and act. And fighter pilots who can do it the fastest should win the aerial dogfight if they make good use of their energy and airspeed. Even if you borrowed it to discuss the best way to program a UAS (Unmanned Aerial Vehicle System) to complete a task or mission, it’s good advice.
In one paper, “Model-Based Video Stabilization of Ultra-Small Airplanes in Real Time,” the summary states: “The new branch of micro air vehicles (MAVs) has received a lot of interest in indoor navigation capabilities, but remote or autonomous tasks require high-quality video. A common problem with in-vehicle video quality is It is an unwanted movement and there are various approaches to solving it with mechanical or video stabilizer software. Few video stabilizer software can be applied in real time and their algorithms take into account the intentional movement of the teleoperator. I have not.”
Sure, this is a problem, and if you want to deliver a package or send a drone to perform an autonomous mission, whether you work as a flight guard at a commercial construction site, for example, it’s true. Is the problem.
The treatise continues to suggest ways to solve some of these challenges. “A new technology has been introduced for real-time video stabilization at low computational cost without generating false motion or degrading performance. Conversion to get robust interframe motion estimates. And outlier rejection, and a Kalman filter based on a dynamic model. “
Now, there are people working on these things, but the desire to allow drones to operate autonomously in a safe and efficient way until sensors, imaging, and equipment are good at such tasks. It is clear that this cannot be achieved. Expected benefits of these technologies in the future. I would appreciate it if you could consider my thoughts here and some of my recommendations to borrow a strategy from nature to achieve such a goal.
Quote:
A.) “Visual-based detection and distance estimation of micro unmanned aerial vehicles” by Fatih Gokce, Gokturk Ucoluk, Erol Sahin and Sinan Kalkan. Sensor 2015, 15 (9), 23805-23846; Doi: 10.3390 / s150923805
B.) Treatise: “Fast Object Tracking with Local Binary Features” by Breton Lawrence Minnehan of Rochester Institute of Technology. July 2014.
C.) “Model-based video stabilization of micro-airplanes in real time” by Wilbert GAguilar and Cecilio Angulo.
D.) “Real-time Megapixel Multispectral Bioimaging” by Jason M. Eichenholz, Nick Barnetta, Yishung Juanga, Dave Fishb, Steve Spanoc, Erik Lindsleyd, Daniel L. Farkasd.
E.) “Extended tracking system based on microinertia measurement unit for measuring sensorimotor response of pigeons” by Noor Aldoumani, Turgut Meydan, Christopher M Dillingham, and Jonathan TErichsen.
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