Autonomous Systems Photo Collage

Autonomous Systems

Autonomous systems operate in complex, open-ended environments with a high level of independence and self-determination. They have the ability to perceive, learn and act with self-awareness and respond intelligently to unforeseen changes in the environment. We believe such systems have the potential to deeply impact society.

This area of study will integrate faculty expertise from Mechanical and Aerospace Engineering, Electrical and Computer Engineering and Computer Science.

The curriculum will focus on recent advances including dynamic systems and controls, machine learning, optimization, and embedded and cyber-physical systems. It will also explore important autonomous system technologies including robotics, autonomous electric vehicles, transportation network, smart grids, etc.

Area Director: Prof. T.C. Tsao

“The curriculum is designed to cover a wide spectrum of autonomous systems — from self-driving cars to unmanned aircraft systems. Students will get a chance to learn and explore the latest developments impacting such systems.”

Area Director: Prof. T.C. Tsao

 

Sample Curriculum

Fall Winter Spring Summer
MECH&AE 270A
Linear Dynamical Systems

(Instructor: R. M’Closkey)
MECH&AE 277
Linear Optimal Control

(Instructor: T-C. Tsao)

EC ENGR 232D
Communications Networking and Traffic Management for Autonomous Mobile Systems

(Instructor: I. Rubin)

or

MECH&AE 298
Autonomous Electric Vehicles

(Instructor: R. Gadh)

Capstone Project
EC ENGR M202A
Embedded Systems

(Instructor: M. Srivastava)
EC ENGR/COM SCI M146 Introduction to Machine Learning

(Instructor: TBD)
Engineering Professional Development Elective Engineering Professional Development Elective
Engineering Professional Development Elective      
12 Units 8 Units 8 Units 8 Units

 

Sample Curriculum Options

Fall Winter Spring Summer
MECH&AE M270A MECH&AE 277 MECH&AE 298 Capstone Project
EC ENGR/COM SCI M146 EC ENGR C247 Engineering Professional Development Elective Engineering Professional Development Elective
Engineering Professional Development Elective      

 

Fall Winter Spring Summer
MECH&AE M271A EC ENGR/COM SCI M146 MECH&AE 273A Capstone Project
MECH&AE C237 EC ENGR 232B Engineering Professional Development Elective Engineering Professional Development Elective
Engineering Professional Development Elective      

 

Fall Winter Spring Summer
EC ENGR 236A MECH&AE 263B MECH&AE 263C Capstone Project
EC ENGR M202A Engineering Professional Development Elective EC ENGR/COM SCI 232D Engineering Professional Development Elective
Engineering Professional Development Elective      

 

Prerequisites (Subject to Change)

All colored classes were offered in F/W/S 2020. Purple means no prerequisite to take the class. Green has a prerequisite in a purple class. Blue has a prerequisite in a green class.


  1. At least three classes in fundamental knowledge of autonomous systems, which covers at least two areas:
    • Dynamic Systems and Control:
      • MECH&AE M270A/EC ENGR M240A/CHE M280A (F) Linear Dynamical Systems
      • MECH&AE 270B (W) Linear Optimal Control
      • EC ENGR M242A/CHEM282A/MECH&AE M272A (W) Nonlinear Dynamic Systems
      • MECH&AE 273A (S) Robust Control System Analysis and Design
    • Estimation, Learning, Adaptation:
      • MECH&AE C271A/EC ENGR 241A (F) Probability and Stochastic Processes in Dynamical Systems
      • EC ENGR 246 (W) Foundation of Statistical Machine Learning
      • EC ENGR M146/COM SCI M146 (F/W) Introduction to Machine Learning
      • MECH&AE 271B (W) Stochastic Estimation
      • EC ENGR C247 (W) Neural Network and Deep Learning
      • MECH&AE C298 (S) Autonomous Electric Vehicles
      • EC ENGR 210A (S, cancelled) Adaptation and Learning
      • COM SCI 260 (S) Machine Learning Algorithms, prereq.
      • COM SCI 180, restricted to COM SCI
    • Optimization:
      • EC ENGR 236A (F) Linear Programming
      • EC ENGR 236B (W) Convex Optimization
    • Embedded and Cyber-Physical Systems
      • EC ENGR M202A/COM SCI M213A (F)
      • EC ENGR M202B/COM SCI M213B. Energy-Aware Computing and Cyber-Physical Systems
  2. At least one class in applications, experiment or design of autonomous systems:
    • Control Systems:
      • MECH&AE 172B (W) Control Systems Design Laboratory
      • MECH&AE 277 (W) Advanced Digital Control for Mechatronic Systems
      • MECH&AE 171B (S) Digital Control of Physical Systems
    • Robotic Systems:
      • MECH&AE 263A (F) Kinematics of Robotic Systems
      • MECH&AE 263B (W) Dynamics of Robotic Systems
      • MECH&AE 263C (S) Control of Robotic Systems
    • Infrastructures:
      • MECH&AE C237 (F) Design and Analysis of Smart Grids
      • MECH&AE 298 (S) Autonomous Electric Vehicles (new class)
      • EC ENGR 232B (W) Queueing Systems and Intelligent Transportation Network
      • EC ENGR 232D (S) Communications Networking and Traffic Management for Autonomous Mobile Systems.
    • Embedded and Cyber-Physical Systems:
      • EC ENGR M202C Networked Embedded Systems Design