A low-budget DIY autonomous lane keeping system
Despite too confident proclamations Since high profile players In THE technology And automobile Industries, were always A long path Since fully autonomous autonomous driving cars. Current prototypes work GOOD below ideal terms, but are easily thwarted by every day real world anomalies. way keeping, However, East A a lot more approachable challenge And Computer scientist was able add such Functionality has A older vehicle.
A lot of Today cars to have way keeping aptitude And that generally works by look has THE way lines on THE road. Because cable driven East NOW THE standard, THE vehicle can direct himself has stay In THE lines. That works GOOD on highways And the highways, because he only needs has perform little adjustments without any of them turns. This DIY way keeping system works In A slightly different path. He looks has THE entire scene In in front of THE car And uses A AI has determine if he should adjust THE direction.
Before keep on going, he East value noting that Computer scientist research has accent that This East not on For to use In THE real world. There are Also a lot potential security problems And he would be require extensive essay Before he would be be responsible has even to try he on A public road.
With that In spirit, This of the system performance was only simulated. He uses A qualified convolutional neural network (CNN) has indicate how THE the car would himself if he had real control on THE piloting. Computer scientist qualified that CNN using A laptop, A webcam, And A Arduino Nano 33 IoT. THE computer recordings video executives while Also registration THE orientation of THE Arduino through It is integrated six axes IMU. With THE advice attached has THE piloting wheel, that orientation corresponds has THE corner of THE piloting wheel.
Through THE Magic of machine learning, THE CNN was able has partner types of imagery with piloting angles. SO he could see A bend In THE road And know that that means THE piloting wheel needs has turn.
"Can You reproduce millions of dollars of technology with A webcam And A Arduino? Not Really, but You can get pretty shut up!”
As Computer scientist watch, This works enough GOOD. But he East Also easily confused. He would be take A plot more training data In A bigger variety of terms has produce A reliable system. In theory, However, such A system would be be more robust that standard way keeping systems that look has road lines.
Despite too confident proclamations Since high profile players In THE technology And automobile Industries, were always A long path Since fully autonomous autonomous driving cars. Current prototypes work GOOD below ideal terms, but are easily thwarted by every day real world anomalies. way keeping, However, East A a lot more approachable challenge And Computer scientist was able add such Functionality has A older vehicle.
A lot of Today cars to have way keeping aptitude And that generally works by look has THE way lines on THE road. Because cable driven East NOW THE standard, THE vehicle can direct himself has stay In THE lines. That works GOOD on highways And the highways, because he only needs has perform little adjustments without any of them turns. This DIY way keeping system works In A slightly different path. He looks has THE entire scene In in front of THE car And uses A AI has determine if he should adjust THE direction.
Before keep on going, he East value noting that Computer scientist research has accent that This East not on For to use In THE real world. There are Also a lot potential security problems And he would be require extensive essay Before he would be be responsible has even to try he on A public road.
With that In spirit, This of the system performance was only simulated. He uses A qualified convolutional neural network (CNN) has indicate how THE the car would himself if he had real control on THE piloting. Computer scientist qualified that CNN using A laptop, A webcam, And A Arduino Nano 33 IoT. THE computer recordings video executives while Also registration THE orientation of THE Arduino through It is integrated six axes IMU. With THE advice attached has THE piloting wheel, that orientation corresponds has THE corner of THE piloting wheel.
Through THE Magic of machine learning, THE CNN was able has partner types of imagery with piloting angles. SO he could see A bend In THE road And know that that means THE piloting wheel needs has turn.
"Can You reproduce millions of dollars of technology with A webcam And A Arduino? Not Really, but You can get pretty shut up!”
As Computer scientist watch, This works enough GOOD. But he East Also easily confused. He would be take A plot more training data In A bigger variety of terms has produce A reliable system. In theory, However, such A system would be be more robust that standard way keeping systems that look has road lines.
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