OVERVIEW

The Course introduces to optimization models and methods for the solution of decision problems, with particular attention to models and problems arising in Robotics Engineering. It is structured according to the basic topics of problem modelling, its tractability, and its solution by means of algorithms that can be implemented on computers. 

AIMS AND CONTENT

LEARNING OUTCOMES

The lecture presents different theoretical and computational aspects of a wide range of optimization methods for solving a variety of problems in engineering and robotics.

AIMS AND LEARNING OUTCOMES

The Course aims at providing the students with the skills to deal with engineering problems, with particular emphasis on Robotics Engineering, by developing models and methods that work efficiently in the presence of limited resources.

The students will be taught to: interpret and shape a decision-making process in terms of an optimization problem, identifying the decision-making variables, the cost function to minimize (or the figure of merit to maximize), and the constraints; framing the problem in the range of problems considered "canonical" (linear / nonlinear, discrete / continuous, deterministic / stochastic, static / dynamic, etc.); realizing the "matching" between the solving algorithm (to choose from existing or to be designed) and an appropriate processing software support.

TEACHING METHODS

Lectures and exercises

SYLLABUS/CONTENT

Introduction. Optimization and operations research for Robotics.

Linear programming

Integer linear programming

Nonlinear programming

Graph optimization

N-stage optimization and dynamic programming

Putting things together: models, methods, and algorithms of operations research for the optimisation of robotic systems

Software tools for optimization

RECOMMENDED READING/BIBLIOGRAPHY

Lecture notes provided by the teacher

TEACHERS AND EXAM BOARD

Exam Board

MARCELLO SANGUINETI (President)

RENATO UGO RAFFAELE ZACCARIA (President)

MAURO GAGGERO

MASSIMO PAOLUCCI

LESSONS

LESSONS START

Sempember 19, 2017

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

Exam schedule