Autonomous Unmanned Aerial Vehicles
Autonomous Unmanned Aerial Vehicles means that the Unmanned Aerial Vehicle can make decision based on the data that it has onboard the computer processors or the data that it retrieves during the flight, independent of the pilot giving complete information instructions. Autonomous can also mean that the Aerial vehicle is actively engaged with the various optic monitors and processors on assigned moving subject on the ground. The task of following a subject initially given by the pilot.
New series debut has been introduced in the latest product from DJI Phantoms 4 series.
It has many new features and to name two of the main ones they are, machine learning and computer vision, for autonomous flying. The Phantom 4 is capable of sensing its environment and able to avoid colliding with obstructions along its flight path. It can simply stop before the obstacle even when the pilot may be giving it instructions for full speed ahead. It can also go over the obstacle by flying up and over.
How does it work? Autonomous Unmanned Aerial Vehicles
I don’t know how the new Phantom 5 optic sensors work with the on board processor but there are some clues how it works in theory. Here are some parallel comparisons from other industries like autonomous robotics to create artificial intelligence.
In theory one can imagine other vehicles where autonomous vehicles have been trialed; the most obvious one that comes to mind is the autonomous motor vehicle. Here is information that I discovered from Wikipedia.
“An autonomous car (driverless car, self-driving car, robotic car is a vehicle that is capable of sensing its environment and navigating without human input”.
So there you have it, the Autonomous vehicles detect the surroundings using the following:
- Computer vision.
“Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage. Autonomous cars have control systems that are capable of analyzing sensory data to distinguish between different cars on the road, which is very useful in planning a path to the desired destination”
So what is radar?
Radars have been used for the last 70 years and the technology is widely used for all sorts of things aviation and on ground purposes.
“Radar is an object-detection system that uses radio waves to determine the range, angle, or velocity of objects. It can be used to detect aircraft, ships, spacecraft, guided missiles, motor vehicles, weather formations, and terrain”.
What about Lidar?
Have you ever heard of the word before? It sounds like an endangered reptile.
“Lidar (also written LIDAR, LiDAR or LADAR) is a surveying technology that measures distance by illuminating a target with a laser light. Although thought by some to be an acronym of Light Detection And Ranging, the term lidar was actually created as a portmanteau of “light” and “radar”. Lidar is popularly used as a technology to make high-resolution maps, with applications in geodesy, geomatics, archaeology, geography, geology, geomorphology, seismology, forestry, atmospheric physics, airborne laser swath mapping (ALSM) and laser altimetry. What is known as Lidar is sometimes simply referred to as laser scanning or 3D scanning, with terrestrial, airborne and mobile applications”.
The Global Positioning System.
The GPS has become a common house hold name in the last 20 years, most people understand it by now.
“The Global Positioning System (GPS) is a space-based navigation system that provides location and time information in all weather conditions, anywhere on or near the Earth where there is an unobstructed line of sight to four or more GPS satellites. The system provides critical capabilities to military, civil, and commercial users around the world. The United States government created the system, maintains it, and makes it freely accessible to anyone with a GPS receiver”.
What about Odometry? O- do-metrics?
“Odometry is the use of data from motion sensors to estimate change in position over time. Odometry is used by some robots, whether they be legged or wheeled, to estimate (not determine) their position relative to a starting location. This method is sensitive to errors due to the integration of velocity measurements over time to give position estimates. Rapid and accurate data collection, equipment calibration, and processing are required in most cases for odometry to be used effectively”.
Computer vision is analytical process of measuring the environment numerically.
“Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions. A theme in the development of this field has been to duplicate the abilities of human vision by electronically perceiving and understanding an image”.
Here are some more ideas on the subject.
“Sub-domains of computer vision include scene reconstruction, event detection, video tracking, object recognition, object pose estimation, learning, indexing, motion estimation, and image restoration”.
“Areas of artificial intelligence deal with autonomous planning or deliberation for robotically systems to navigate through an environment. A detailed understanding of these environments is required to navigate through them. Information about the environment could be provided by a computer vision system, acting as a vision sensor and providing high-level information about the environment and the robot”.
It all sound like a FUN DIY Project, right?
If you are not so keen to try and build your own Autonomously flying UAV, then perhaps you may be interested in the DJI Phantom 4 Series? Where they have done al the hard work in designing and creating the complete product ready to fly out of the box.
See the PHANTOM 4 IN ACTION.
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