Industry Course – Robot Autonomy – Course by Prof. Kirill Solovey

The course is intended for a non technion audience – engineers, researchers, and those interested in the field from the industry.

 In this course, we dive into the intelligence behind self-driving cars, racing drones, multi-robot swarms, and other cutting-edge autonomous systems. These technologies rely on diverse algorithms that enable robots to perceive their environment, make decisions, and execute actions with precision and efficiency, all of which we will explore in this class. In addition to providing crucial theoretical knowledge, we will gain practical insights about getting those methods to work in the real world and learn about hardware considerations through live demos of racecars and quadcopters.

May 25-26, 2025

9:00-16:00

Course Overview

This course provides a deep dive into the core autonomy stack of robotic systems, balancing theoretical principles with hands-on implementation. We begin with fundamental concepts in robot dynamics and progress through essential techniques in control, planning, and estimation. The course also covers advanced topics in multi-robot systems and smart mobility, culminating in practical demonstrations on robotic hardware. Whether you aim to develop self-driving cars, autonomous drones, or collaborative robot teams, this course will equip you with the necessary tools to tackle real-world autonomy challenges.

Course syllabus:

• Kinematics and dynamics of mobile robots and manipulators. Robot control: PID, pure pursuit, LQR, model-predictive control.
• Motion planning: Configuration spaces, probabilistic roadmaps, rapidly-exploring random trees, and advanced kinodynamic planners
• Estimation: Localization using extended Kalman and particle filters, simultaneous localization and mapping (SLAM)
• Advanced topics: Autonomous racing and driving, multi-robot systems, smart mobility
• Practical aspects: Robotic operating system (ROS), hardware considerations, hardware demos of ground and aerial vehicles.