MAE6790 | Intelligent Sensor Planning and Control

Silvia Ferrari
Department of Mechanical and Aerospace Engineering
Cornell University

Course Description

An introductory course on learning and intelligent-systems techniques for the modeling, planning, and control of dynamic sensors. Methods for intelligent sensor fusion, sensor management, and mobile sensor navigation and control will be covered in detail in this course. Topics also include neural networks, Bayesian networks, and information theory, as they apply to problems drawn from environmental monitoring, sensor path planning, sensing-and-pursuit games, target tracking, classification, and satisficing searches.

Course Outline

  • Introduction

Scope of the course
Motivating Sensing Applications

  • Sensor Modeling

Platform dynamics
Sensor Field-of-View (FoV)
Sensor Measurements
Environmental Variability and Feedback

  • Sensor Performance and Estimation

Probability of Detection and False Alarms

  • Sensor Placement, Navigation, and Control

Placement Optimization
Path Planning
Trajectory Optimization
Integrated Control and Navigation

Elements from the following topics will be reviewed throughout the semester:
Linear systems, systems theory, graph theory, probability theory, information theory, optimal control, and planning.

Principal Sources


Silvia Ferrari and Tom A. Wettergren Information-driven Planning and Control, CRC Press, to appear in 2017


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