Preser

A Matlab Framework For Professional Education in Service Robotics

The project

The object of the project is to develop and test the new area of Professional Education in Service Robotics. The main motivation comes from the fact that there is a significant gap between research education and professional education, i.e. addressing the needs of integrators of service robots.

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3 Years

The project started in 2017 and lasts for three years.

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Theory lessons

Mapping; Localization; Navigation; Visual computing; Object manipulation; Teleoperation; Communication.

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Practical lessons

Software setup; Sensors; Safety; Image segmentation; Grasping; Teleoperation; Algorithms.

Preser Project

PRESER will provide lectures for addressing the practical aspects of using a service robot in a domestic environment and a simulation framework based on MATLAB^®and the simulator V-REP for testing your knowledge during the lessons.

Download Preser

Our framework is available for OSX, Windows and Debian based distros. You can download the binary included in Preser for free following the button below, or you can get the source code via our public repositories. Click here to follow step-by-step instructions for setting up Preser on your computer (Mac OS X, Windows, Linux) and connecting it to the simulator.

Download binaries

Download source code

Sketch

The Sketch section gives you a brief description for the built-in examples of what you can do with Preser. If you want to get some information about the principles, techniques and how to setup the framework read the User manual.

Slam (Simultaneous localization and mapping)

Map building Build a real-time map of the environment.
Map building and planning Build a real-time map of the environment and plan a route to a specific destination.

Localization

Localization Move and localize your robot on a static map.

Planning

Planning Plan a route to a specific destination on a static map.
Trajectory Plan a route to a specific destination and move the robot to a specific destination on a static map.

Extra

Planimetry Build a simulator scene from a provided planimetry of the environment.
Trajectory 2 Use together trajectory generator and free robot navigation.

Object recognition and identification

Image segmentation Use standard segmentation algorithms.
Object identification Identify object in the scene.
Active Sensing Move robot in different pose to acquire images.

Grasp planning

Geometry Use inverse kinematic to grasp from a point given by segmentation.
Agile Grasp Use the agile grasp algorithm.

Visual servoing

Camera calibration Use MATLAB^® camera calibration and load parameters.
Visual Navigation and servoing. Define trajectory.

Extra

Navigation and grasping Build a simulator scene in an office environment which use navigation algorithm and object grasping.

Teleoperation

Four Channel Teleoperation architecture.
Two Layer Energy tank teleoperation algorithm.
TDPA Time Domain Passivity Approach.

Acknowledgments

Preser is a IEEE RAS-Funded Project CEMRA (Creation of Educational Material in Robotics and Automation)