Since Google introduced AlphaGo, the artificial intelligence program has gained widespread attention. AlphaGo was the first AI to defeat a world champion in the ancient game of Go. According to recent reports, Google is now focusing on "hard" technology, and this time it's about AI-powered drones.
Known for its strong software capabilities but limited hardware experience, Google has partnered with NASA’s Jet Propulsion Laboratory (JPL) to leverage their advanced engineering skills. Together, they are developing fully autonomous small drones. It's hard not to speculate—after AlphaGo, will Google create an "AI chicken"?
JPL has combined Google's Tango 3D environment detection technology to build an AI-controlled drone. Recently, they conducted an indoor flight test that included both human and AI pilots. In the race, the AI drone completed a lap in 13.9 seconds, slightly behind the human pilot's 11.1 seconds. However, the AI drone showed greater stability during the flight, while human pilots tended to be more aggressive, accelerating quickly and taking riskier routes.
Manually operated drones typically rely on GPS for navigation, which limits their use in indoor environments. This is where AI-controlled drones have a clear advantage, as they can operate without GPS signals, making them ideal for use in warehouses or dense urban areas. These drones are completely autonomous, meaning they don’t depend on external positioning systems or remote computers. Instead, they make decisions on their own to find the optimal flight path.
One major challenge in fast indoor flight is the camera's shutter speed, which affects how well the drone tracks its movement. Flying too fast, too close to the ground, or rotating too quickly can lead to blurry images or even loss of control. To address this, JPL has implemented two key solutions: first, using two wide-angle cameras—one pointing forward and one downward—to give the drone a field of view exceeding 250 degrees. Second, adjusting the drone’s flight path to limit rotation speed and maintain a safe ratio between altitude and velocity.
The main limitations in AI drone development today are still camera technology and AI algorithms. Advanced cameras act as the drone's "eyes," allowing it to keep up with rapid movements. Meanwhile, improved AI algorithms function as a stronger "brain," enabling the drone to learn and analyze the best flight paths quickly. With JPL’s hardware expertise and Google’s software background, this AI drone has the potential to outperform human-operated ones.
In summary, as AI technology continues to evolve, AI drones are set to play a bigger role in various real-world applications. Beyond indoor environments, they could be used in search and rescue missions in deep forests or mountainous regions, disaster response, and even in flood-prone areas. The future of AI drones looks promising, and we're only beginning to see their full potential.
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