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Foundations of Autonomous Systems

Offered By: University of Colorado Boulder via Coursera

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Course Description

Overview

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This specialization provides a comprehensive overview of designing and analyzing autonomous systems. It begins with an examination of fundamental components like sensors, actuators, and communication networks, then delves into formal modeling frameworks such as state-space representations, timed automata, and hybrid automata. Then formal modeling of system requirements, including stability, reachability, and specifications framed by linear temporal logic formulas is discussed. Verification techniques such as Lyapunov theories and model checking are explored, followed by a segment on synthesizing controllers to enforce specified properties, employing techniques like finite abstraction construction and controller refinement. Courses in this specialization can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Syllabus

Course 1: Modeling of Autonomous Systems
- Offered by University of Colorado Boulder. This course will explain the core structure in any autonomous system which includes sensors, ... Enroll for free.

Course 2: Requirement Specifications for Autonomous Systems
- Offered by University of Colorado Boulder. This course will discuss different ways of formally modeling requirements of interest for ... Enroll for free.

Course 3: Verification and Synthesis of Autonomous Systems
- Offered by University of Colorado Boulder. This course will provide different techniques on the verification of autonomous systems against ... Enroll for free.


Courses

  • 0 reviews

    8 hours 39 minutes

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    This course will explain the core structure in any autonomous system which includes sensors, actuators, and potentially communication networks. Then, it will cover different formal modeling frameworks used for autonomous systems including state-space representations (difference or differential equations), timed automata, hybrid automata, and in general transition systems. It will describe solutions and behaviors of systems and different interconnections between systems. This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
  • 0 reviews

    10 hours 48 minutes

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    This course will discuss different ways of formally modeling requirements of interest for autonomous systems. Examples of such requirements include stability, invariance, reachability, regular languages, omega-regular languages, and linear temporal logic properties. In addition, it will introduce non-deterministic finite and büchi automata for recognizing, respectively, regular languages and omega-regular languages. This course can be taken for academic credit as part of CU Boulder’s MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
  • 0 reviews

    10 hours 51 minutes

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    This course will provide different techniques on the verification of autonomous systems against stability, regular, or omega-regular properties. Such techniques include Lyapunov theories, reachability analysis, barrier certificates, and model checking. Finally, it will introduce several techniques on designing controllers enforcing properties of interest over the original autonomous systems. This course can be taken for academic credit as part of CU Boulder’s Masters of Science in Computer Science (MS-CS) degrees offered on the Coursera platform. This fully accredited graduate degree offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

Taught by

Majid Zamani

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