3D Road Surface Reconstruction

This lecture overviews 3D Road Surface Reconstruction that has many applications in autonomous car vision and smart city infrastructure inspection. It covers the following topics in detail: Road Surface Reconstruction: Active-sensing-based methods (Laser scanning-based methods, Microsoft Kinect), Passive sensing-based methods (Shape from Shading, Stereo vision). Road Infrastructure reconstruction, SfM for cliff surface reconstruction.

Pedestrian Detection

This lecture overviews Pedestrian Detection  that has many applications in autonomous car vision and smart city applications. It covers the following topics in detail: Self-driving car architecture, Pedestrian state estimator, Crosswalk state estimator, CNN pedestrian detection and tracking, Pedestrian Trajectory Estimation.

Autonomous Car Modeling and Control

This lecture overviews Autonomous Car Modeling and Control that has many applications in autonomous cars and automated driving. It covers the following topics in detail: Car Dynamic Models (Car-Body Dynamics – The Slow Dynamics, Tire Dynamics – The Fast Dynamics). Kinematic Models (System Equations, Bicycle – Car Kinematic Model). Point – Mass Models. Autonomous Vehicle Control Techniques (Model Predictive Control Law, Pure Pursuit Control Law, Stanley Control Law, Modified Sliding Mode Control Law, Kinematic Lateral Speed Control Law). Deep Autonomous Vehicle Control.

Autonomous Car Sensors

This lecture overviews Autonomous Car Sensors that has many applications in autonomous car perception. It covers the following topics in detail: Cameras, Lidars. Other sensors: Radars, Ultrasonic transducers, Global positioning system (GPS), Inertial measurement unit (IMU). Signal sensors: coolant temperature sensor, steering angle sensor, throttle position sensor. Traffic sensors: accelerometers, piezoelectric sensors, magnetometers, microwave radars, ultrasonic radars, acoustic sensors, infrared light sensors, video cameras.

Introduction to Autonomous Car Vision

In this lecture, an overview of the autonomous car technologies will be presented (structure, HW/SW, perception), focusing on car vision. Examples of autonomous vehicle will be presented as a special case, including its sensors and algorithms. Then, an overview of computer vision applications in this autonomous vehicle will be presented, such as visual odometry, lane detection, road segmentation, etc. Also, the current progress of autonomous driving will be introduced.

Robot Kinematics and Dynamic Modeling

This lecture overviews Robot Kinematics and Dynamic Modeling that has many applications in robotic control. It covers the following topics in detail: Robot Kinematics: Kinematic Equations, Forward kinematics, Inverse kinematics, Rotations. Dynamic Modeling, Robot Dynamics. Foundations from Classical Mechanics, Newton-Euler Method, Lagrange Method.