Lectures
You can download the lectures here. We will try to upload lectures prior to their corresponding classes.
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Introduction to Autonomous Driving: Perception, Planning Control
tl;dr: Course introduction and logistics. Brief introduction to topics covered.
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Suggested Readings: Tutorial 1: Intorduction to ROS2.
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Automatic Emergency Braking
tl;dr: Introduction to AEB and range sensors.
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Suggested Readings: Tutorial 2: Intorduction to the F1tenth Simulator.
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Rigid Body Transformations
tl;dr: Frames of references and rigid body transformations. Using tf2_ros.
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Suggested Readings: Tutorial 3: ROS2 and TF2.
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Vehicle States, Dynamics, and Simulation
tl;dr: Dynamics states, single track models, tire models.
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Localization: Particle Filter
tl;dr: Mapping, localization, AMCL and particle filter Tuning.
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Introduction to Graph-based SLAM
tl;dr: Graph SLAM, Probability and Scan Matching, Sparse Pose Adjustment
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Suggested Readings: Tutorial 5: Running slam_toolbox and pf
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Local Planning: RRT, Spline Based Planner
tl;dr: Obstacle avoidance using sampling based planners
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Optimization & Control I: Optimization Basics and LQR
tl;dr: Introduction to optimization, optimal control and MIMO systems.
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Optimization & Control II: Optimization Basics and LQR
tl;dr: Introduction to constrained optimal control, MPC formulation and application.
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Introduction to Autonomous Driving: Perception, Planning Control
tl;dr: Deep Learning Basics, Object Detection, and Network Deployment.
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Ethics
tl;dr: In-class discussion on ethics and autonomous vehicles.
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Suggested Readings: Tutorial 6: Foxglove visualization for the F1tenth
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Raceline Optimization
tl;dr: Shortest Path, Minimum Curvature, Minimum Time and evolution strategies.
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Reinforcement Learning and Imitation Learning
tl;dr: Reinforcement learning basics and applications on F1tenth.
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Suggested Readings: Tutorial 7: Implementing RL on the F1tenth
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Race 1 Preparation
tl;dr:
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Race 3 Preparation
tl;dr:
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