Perhaps the biggest demand for consumer drones today is the obstacle avoidance of drones. It is good to let the drone follow you in accordance with the pre-designed flight path, but if the drone hits the obstacle in the middle, then this will be a costly lesson. This is not to say that an accident can occur in automatic flight, and the drone operator can actively avoid accidents like a car driver, but the drone also needs a safety system to prevent accidents.
Can the machine learn to avoid obstacles in the future?
Obstacle avoidance seems to be a small step on the real intelligent automated flight path. Yes, we want the drone to find ways to avoid them when they detect obstacles, but our ultimate goal is to let the drone understand the surrounding environment and make adjustments during the flight, just like professional The pilot did the same when flying.
At present, the Elves 4 in Dajiang are in the forefront of the industry in terms of obstacle avoidance, and the biggest competitor of the Chinese drone giant, Li Xiang, is about to release TyphoonH. Both UAVs have obstacle avoidance systems, and they are not flying. It is likely to collide directly with the object. However, the obstacle avoidance system of Dajiang Elf 4 may sometimes make mistakes. Yes, DJI's technology can avoid a lot of accidents, but it is prone to errors when dealing with obstacles beside and behind, and it is easy to encounter problems when identifying smaller obstacles. Dajiang’s obstacle avoidance technology is still in the process of progress and cannot be called perfection at present. Obstacle avoidance is also a thing that can be improved by the soaring TyphoonH. In this year's CES conference demonstration, TyphoonH is equipped with Intel's RealSense, which seems to be a more comprehensive obstacle avoidance system, which can even make flight path adjustments based on moving objects.
Soaring TyphoonH can do better in avoiding obstacles.
Intelligent automated flight is not far away
So what will be the next step in the development of obstacle avoidance? We introduced Skydio not long ago, and the company is constantly improving its system so that drones can map the surroundings and then make intelligent choices. This system can do more than just detect obstacles around it. . Skydio's CEOAdamBry said that their drones are not only avoiding obstacles, they will make full use of the existing surrounding environment information, and then make intelligent choices, just like the performance of professional pilots.
At present, it seems that letting the machine learn independently will be the future development direction. Soon after, the consumer-class drones will have a more comprehensive understanding of the surrounding environment. The more they fly, the more they can learn about the surrounding world. Information. This dynamic sensing technology is currently being developed by RossAllen and MarcoPavone of the Department of Aerospace, Stanford University. They recently published a paper titled "Application of Real-Time Dynamic Programming in Obstacle Avoidance," which states that their systems "explore the surrounding environment through machine learning and make the best control methods." Decision making, prior calculations where possible."
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