Week 2 - Self-Driving Hardware and Software Architectures Course info. https://www.coursera.org/learn/intro-self-driving-cars? UNIVERSITY OF TORONTO Lesson 4 : Environment Representation Contents Environmental Map Types Environmental Map Types Localization of the vehicle in the environment Localization point cloud or feature map to accurately estimate the precise position of vehicle at all time ..

Week 2 - Self-Driving Hardware and Software Architectures Course info. https://www.coursera.org/learn/intro-self-driving-cars? UNIVERSITY OF TORONTO Lesson 3 : Software Architecture Contents Describe the basic architecture of a typical self-driving software system Identify the standard software decomposition Environment Perception Environment Mapping Motion Planning Controller System Supervisor ..

Week 2 - Self-Driving Hardware and Software Architectures Course info. https://www.coursera.org/learn/intro-self-driving-cars? UNIVERSITY OF TORONTO Lesson 2 : Hardware Configuration Design Contents Sensor coverage requirements for differenct scenarios Highway driving Urban driving Overall coverage, blind spots Sensors Camera for appearance input Stereo camera for depth information Lidar for all..

Week 2 - Self-Driving Hardware and Software Architectures Course info. https://www.coursera.org/learn/intro-self-driving-cars? UNIVERSITY OF TORONTO Lesson 1 : Sensors and Computing Hardware Contents Sensor types and characteristics Self-driving computing hardware Sensors Sensor: device that measures or detects a property of the environment, or changes to a property Categorization Exteroceptive ..

Week 1 Course info. https://www.coursera.org/learn/intro-self-driving-cars? UNIVERSITY OF TORONTO Lesson 3. Driving Decisions and Actions Contents Planning : types (window of time), examples Various decisions needed for a simple intersection scenario Type of planning Reactive Predictive Planning : Examples Making decisions Long-term (Entire driving task) (출발지에서 목적지까지의 계획) How to navigate from Ne..

Week 1 Course info. https://www.coursera.org/learn/intro-self-driving-cars? UNIVERSITY OF TORONTO Lesson 2. Requirements for Perception Contents What is perception? Goals for perception Static, dynamic objects Ego requirements Challenges to perception Roughly... Input -> Perception (Analyze ego motion & environment) -> Planning (Decide on and plan a maneuver) -> Drive What is perception? We want..