All Pods / Engineering
Exploring Autonomous Systems: Understanding how autonomous systems think, perceive, plan and act
Exploring Autonomous Systems: Understanding how autonomous systems think, perceive, plan and act
Group size
2-6 students
Outcome
An original research paper on a chosen autonomous system and simulation results
Tuition
$495
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Exploring Autonomous Systems: Understanding how autonomous systems think, perceive, plan and act
Self-driving vehicles, aerial drones, and humanoid robots have revolutionized day-to-day life in the 21st century. As these technologies mature, autonomous systems will disrupt supply chains, highways, and society. In this pod, we will investigate how autonomous systems sense, perceive, plan, and act. Students will learn the mathematical foundations of control theory, program their own computer simulation, and implement an industry-standard control algorithm known as PID Control. In addition, we will discuss emerging technologies such as Machine Learning Control and Computer Vision. After learning these concepts, students will write an original research paper on an autonomous system of their choosing. So, what are you waiting on? Grab a spot in this pod before a robot steals your seat!
Week by week curriculum
Week 1
How do autonomous robots organize their thoughts? We’ll discuss the cornerstones of autonomy including sensing, perception, planning, and actuation. Then, students will brainstorm examples of autonomous systems for their original research paper. Block diagrams will be discussed, and mathematical foundations will be provided as a homework assignment.
Week 2
How does NASA build Space vehicles on Earth? To answer this question, students will learn how to simulate a dynamic system through a provided Python script. We will review the mathematical foundations from last week’s homework. Then, we will derive a mathematical model for a dynamic system and learn how to simulate the system through computer programming. Students will explore what happens to the system response when simulation parameters are adjusted.
Week 3
Are rocket scientists just control freaks in disguise? Students will learn about control theory and how it’s used to fly rockets in space, keep your house warm in the winter, and steer self-driving vehicles on the highway. Block diagrams will be used to differentiate between open-loop and closed-loop control systems. Then, PID Control will be introduced, and students will have the opportunity to implement a control algorithm on their dynamic simulation.
Week 4
Do self-driving vehicles have eyes on the back of their head? In this session, students will be introduced to the concepts of sensing and perception. We will discuss the concept of sensor noise, how it plays an important role in autonomous systems, and how to process it in the real world. A brief discussion will be had on combining measurements from multiple sensors.
Week 5
How is Machine Learning and AI used in Autonomous Systems? We’ll discuss special topics in data-driven control and computer vision. For example, how can a dynamic model be generated purely from sensor data? When should machine learning be used instead of traditional control algorithms, and when should it be avoided? How can we quantify trust in autonomous systems?
Week 6
Students will have the opportunity to present 3-5 slides on their chosen autonomous systems research and receive feedback from their mentor and classmates. Remaining time will be reserved for Q&A.