integrated project course - Örebro universityaass.oru.se/~fpa/old/teaching/ipw-2012.pdf ·...

Integrated Project Course


Implementation and Integrationof Research Results

(HT2012)

Instructors: Federico Pecora, Franziska KlüglSchool of Science and TechnologyÖrebro University<name>.<surname>@oru.se

F. Pecora, F. Klügl – Integrated Project Course, HT2012 1 / 34

<name>.<surname>@oru.se


Outline

1 Introduction and Course Objectives

2 Selected Previous Results (2008–2011)

3 Objective of IPW 2012

4 Implementation and Evaluation

5 Appendix: Lab Rules



Introduction and Course Objectives

Outline









Background and Motivation

Robots at work: productivity and robustness. . .

MALTA project




Background and Motivation

Robots at home: a new frontier for human assistance. . .

PEIS-related projects




From Research Results to Integrated Systems

Research projects rely on integration of techniques

Implementation is usually a key aspect (albeit oftenunder-estimated)

implementation of algorithmssoftware engineering, packaging, documentationmodular design and module interfacingdocumentationtesting, testing, testing, . . .

In the Integrated Project Work, you will be confronted withintegration tasks

stemming from on-going research projects at AASS



Selected Previous Results (2008–2011)

Outline









IPW 2010: Smart NAOs in a Smart Home

To develop a system for navigation and control of a NAO robotin the PEIS Home




IPW 2010: Smart NAOs in a Smart Home

To develop a system for navigation and control of a NAO robotin the PEIS Home

IPW 2010 results




IPW 2009: The Robotic Butler II

Development of a robotic butler service in the PEIS-HOME

1. Walk to the fridge 2. Identify drink 3. Dock the fridge

4. Grasp drink w/ fridge gripper 5. Give drink to NAO 6. Walk to the person




IPW 2009: The Robotic Butler II

Outcome of 2009 was very successful

IPW 2009 results




IPW 2008: The Robotic Butler I

Students had a similar task in 2008. . .

IPW 2008 results



Objective of IPW 2012

Outline









Butlers are out. . . Waiters are in!

Your Task

Develop a robotic waiter whichserves the “most deserving”

human(s)

Based on Scitos A6 TransporterRobot by MetraLabs

Unpacked at AASS on Sep 20, 2012!

Application: the Ängen senior livingfacility




The MetraLabs Scitos A6 Transporter

Tray load detection

Laser range finder

Two Asus Xtion 3D cameras, sonars

Bumpers

Very silent

CogniDrive navigation software2–3cm precision, completely based on laser range finder

MIRA robot operating system and visualization tools




The End Result

The transporter is pre-loaded with kannelbullar

Users in different rooms at AASS compete for a kannelbulle

Signalling desire occurs by gesturing to a Kinect/Xtion

The robot brings kannelbullar to the most deserving, navigatingthrough the AASS corridors




Specific Sub-Tasks

Robot Platform. Set up and operate the Scitos A6 Transporter inAASS

MAS-Based Goal Allocation. Develop agent-based architecture forgoal allocation

Human-Robot Interface. Develop gesture-based interface forsignalling desire




Sub-Task 1: Robot Platform

Set up and operate the Scitos A6 Transporter in AASSC/C++ programminguse of MIRA API for navigation/localization/mapping techniquesdevelopment of waiter robot behaviors




Sub-Task 2: MAS-Based Goal Allocation

Develop agent-based architecture for goal allocationC/C++/Java/. . . programminguse of agent-based coordination techniquesdevelopment of communications infrastructure




Sub-Task 3: Human-Robot Interface

Develop gesture-based interface for signalling desireC/C++ programminguse of Kinect and/or Xtion 3D sensors with MIRA or ROS APIsdevelopment of gesture-based language



Implementation and Evaluation

Outline









Implementation

Each task constitutes a small project

The final result is an integrated system and a demonstration

All sub-tasks strongly oriented towards implementation andprogramming

M1

(week 44)

[1 week] [4 weeks]

(week 39) (week 40)

M2

(week 46)

M0 M3

(week 50)

[2 weeks][4 weeks]

Developmentprototype

Roughsystem

Finalsystem

Ing

red

ien

ts

Human−Robot Interface

Goal Allocation

Robot Platform




Workplan Proposal

M0 — Ingredients: getting to know the components of the system inisolation, understanding what works and what doesn’t

Basic setup decided (e.g., which rooms/corridors to map, whereto place the kinects, etc.)

Robot behaviors can be called programmatically, mapping done

Kinect works in ROS, human pose can be seen

MAS-based task allocation algorithm implemented




Workplan Proposal

M1 — Rough System: a working system incorporating all componentswhere significant simplifications have been made

The robot can navigate to all end positions

Simple gesture-based language established and implemented

MAS-based allocation can post goals to robot




Workplan Proposal

M2 — Development Prototype: a complete prototype showing thesuccessful integration of components

No need to manually trigger the various elements of the system

MAS-based allocation leads to robot motion

HRI works robustly with different people




Workplan Proposal

M3 — Final System: a full system which can be easily demonstratedand repeated

The system can handle contingencies (e.g., navigation fails andhas to be re-attempted)

Success rate of scenario is acceptable (≥ 70%)

Product is packaged into a “one click” demo

Simple user manual allows an external person to operate thedemo




Deliverables

Milestone M0 (w40):Deliverable 1 (report): Detailed implementation plan

Milestone M1 (w44):Deliverable 2a: Internal Demonstration

Deliverable 2b (report): What tasks have been achieved?


Deliverable 3b (report): What tasks have been achieved?


Deliverable 4b: External Demonstration (∼Dec 15th)

Deliverable 4c (report): Three papers (before Xmas)

Deliverable 4d (report): User’s Manual




Evaluation (I)

Evaluation will depend onthe quality / adherence to specification of the final productyour ability to acquire the appropriate competencesyour ability to organize your work on your ownyour ability to work with others (students and supervisors)

Evaluation is individualeven though you are working tightly with other students

Evaluation is on-going

Group work is necessary, but credit must always be givenwhere due!




Evaluation (II)

Output 1 of the project is an integrated running demoto be shown at the end of the year to the AASS staff∼ 50 people, some of whom will be asked to compete forkannelbullar

The demo will not be run by you!you will have the opportunity to explain

Output 2 of the project is a video illustrating the systemshould be suitable for the MRLabSweden Youtube channelshould showcase team work, integration, fun, robustness of result




Other Involved People

The IPW is about integrating state-of-the-art technology

expertise is spread across two labs:

Cognitive Robot Systems, Mobile Robotics and Olfaction

no one knows every aspect of the project

all aspects of the project are covered by someone

IPW is also an exercise in finding the right person to ask. . .

Subhash Sathyakeerthy: Scitos, MIRA, ROS

Amy Loutfi: HRI, Kinect-based gesture recognition

Alessandro Saffiotti: Robot motion / behavior implementation

. . . other researchers, PhD students etc. at AASS!





Thank you!



Appendix: Lab Rules

Outline








Appendix: Lab Rules

Rules

When turning on, always make sure one of the emergency stopbuttons is pressed

Do not release the emergency stop button until you are ready tonavigate and the area is clear

The robot can be used anywhere in AASS

The robot can never be brought outside

When not used, the robot should always be in the lab

NOTE: the G6 is massive and has sharp edges, hence there isserious danger of injury!



Appendix: Lab Rules

Rules (cont.)

If you are not sure about something it is always better to askrather than to test things blindly (this could lead to breaking therobot)

The Scitos should be left charged after use

When the Scitos is charging it should be placed in a stable andsafe position

Use common sense



Appendix: Lab Rules

Rules (cont.)

Never turn off computers

Never disconnect devices without asking FPA/FKL or the personusing the device

Never leave the lab open while not there

Do not share access code(s) with anyone outside the IPW

The bed in the PEIS-HOME is not for sleeping

Keep the labs as tidy as possible


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