Apple’s first publicly disclosed paper on autonomous vehicles has been posted online by the company’s computer scientists. The research describes a new software approach called “VoxelNet” that helps computers detect three-dimensional objects like cyclists and pedestrians while using fewer sensors. Reuters reports: The paper by Yin Zhou and Oncel Tuzel, submitted on Nov. 17 to independent online journal arXiv, is significant because Apple’s famed corporate secrecy around future products has been seen as a drawback among artificial intelligence and machine learning researchers. The scientists proposed a new software approach called “VoxelNet” for helping computers detect three-dimensional objects.
Self-driving cars often use a combination of normal two-dimensional cameras and depth-sensing “LiDAR” units to recognize the world around them. While the units supply depth information, their low resolution makes it hard to detect small, faraway objects without help from a normal camera linked to it in real time. But with new software, the Apple researchers said they were able to get “highly encouraging results” in spotting pedestrians and cyclists with just LiDAR data. They also wrote they were able to beat other approaches for detecting three-dimensional objects that use only LiDAR. The experiments were computer simulations and did not involve road tests.
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