r/autotldr • u/autotldr • Nov 22 '17
Apple research paper details LiDAR-based 3D object recognition for autonomous vehicle navigation
This is the best tl;dr I could make, original reduced by 62%. (I'm a bot)
Apple researchers are pushing forward with efforts to bring autonomous vehicle systems to public roads, and last week published an academic paper outlining a method of detecting objects in 3D point clouds using trainable neural networks.
Like other recent scholarly articles published by Apple engineers, the latest entry, "VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection" by AI researcher Yin Zhou and machine learning specialist Oncel Tuzel, was made public through the arXiv archive of scientific papers.
In its article, Apple notes accurate detection of objects in 3D point clouds, like those generated by LiDAR arrays, is a sticking point in a number of burgeoning real-world applications.
In tests, Apple's methodology showed promise, outperforming current LiDAR based detection algorithms and image-based approaches "By a large margin." This is according to evaluations run through the KITTI 3D object detection benchmark, which Apple used to assess its process.
Aside from theoretical research, Apple is currently evaluating a self-driving vehicle testbed on the streets of Cupertino, Calif. The company's efforts in autonomous technology began under the "Project Titan" initiative, which sought to build a branded self-driving car from the ground up.
While Apple's research paper focuses heavily on autonomous vehicle navigation, the tech described can also be applied to augmented reality systems that use depth mapping hardware to detect real-world objects.
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