Dublin Descriptors

Expected learning outcomes

Knowledge and understanding

Students will learn:

·       What are the main type of mobile robot kinematics and their characteristics in terms of direct and inverse kinematics equations

·       How to structure the autonomous navigation system of mobile robots and autonomous vehicles

·       What are the classical method for trajectory planning, i.e., graph and sample based, and the most common algorithms for trajectory planning

·       What are the most common algorithm for trajectory following and obstacle avoidance

·       What are the most used techniques for localization, mapping and simultaneous localization and mapping (SLAM)

·       What are the common sensors used in robot perception, their pros and cons, their use for autonomous navigation and mapping

·       The Robot Operating System (ROS) framework and how it can be used in the development of autonomous robots

Applying knowledge and understanding

Given a specific domain design for a mobile robot, the student will be able to:

·       Design the system architecture for the autonomous navigation of the robot, its modules, and their algorithms

·       Implement the software system controlling a modern autonomous robot based on the ROS middleware

·       Design and develop SLAM algorithms for simultaneous localization and mapping

·       Derive the kinematic equation for a mobile robot, develop the corresponding odometry system and integrate its outcome into a localization or SLAM system

Making judgments

Given an autonomous robot design problem, students will be able to:

·       Identify the proper kinematics for the robot to be developed

·       Identify the proper sensors the robot should have to fulfill its task

·       Select the most appropriate algorithms for trajectory planning and trajectory following

·       Select the most appropriate approach for SLAM, localization or mapping

Communication

The student will learn to:

·       Discuss in written form the pros and cons of different kinematics in the realm of a specific design problem

·       Describe the learned algorithms in written form, discussing their pros and cons.

Lifelong learning skills

Student will learn to:

·       Face the design of the software system for an autonomous robot with a sound background and well defined patterns

·       Develop the software controlling an autonomous robot/vehicle based on the ROS middleware and simulate it under Gazebo

Type of assessment

Description

Dublin descriptor

Written test

The solution of practical and design problems

·       Computation of kinematics equations for a mobile robot and the corresponding odometry

·       Compute the shortest trajectory with a graph based planning algorithm

Answer to theoretical questions

·       Describe and discuss the pros and cons of different trajectory planning algorithms together with their functioning

·       Describe and discuss the pros and cons of different trajectory following and obstacle avoidance algorithms together with their functioning

·       Describe and discuss the pros and cons of different SLAM algorithms together with their functioning

·       Describe the architecture and the functioning of ROS 

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Assessment of practical homework

Execution of a practical project

·       Design of some ROS components implementing navigation capabilities for an autonomous mobile robot

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