10:30AM-1:30PM (PST), Aug 27, 2021

Organizers & Speakers

Overview

This tutorial aims to give an overview of 3D sensing techniques, methodologies, algorithms and systems for a variety of applications in autonomous vehicles and smart cities. The tutorial starts by introducing various 3D sensing mechanisms and devices including lidar, stereo camera, radar, as well as basic sensor fusion. Next, the tutorial discusses current 3D sensing and perception problems and tasks using these sensors. These tasks range from object detection, to segmentation, 3D shape manipulation, motion prediction, mapping, odometry and geometry, and robot navigation and control. For these tasks, the tutorial will then cover some of the state-of-the-art approaches using different 3D sensing modalities, for example, widely used point cloud processing backbones, as well as task-specific methods, such as semantic and instance segmentation, simultaneous localization and mapping (SLAM) and path planning. Also, leveraging these 3D sensing capabilities, the tutorial will discuss some example end-to-end systems from recent literature that explore collaborative sensing and control. The tutorial includes an invited talk from Waymo about the latest lidar perception technology being deployed in real-world autonomous vehicles. Finally, the tutorial concludes with entry points for the audience to get their hands dirty: an overview of a plethora of available simulation tools and evaluation methods and benchmarks, with a deep dive demo, using one example photorealistic simulator, Carla, to demonstrate how to use 3D sensors, experiment with custom scenarios, visualize and process data, and drive vehicles autonomously.