DEFINITION OF DISTRIBUTED, MOBILE AND ROBOTICS

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Why use a DMR system?

Advantages

There are many advantages of using DMR systems described in the literature.
Economically
Constructing a single multi-purpose robot costs more in time and money than creating multiple single -purpose robots [7].
Robustness & Reliability
A distributed solution with multiple robots compared to a single robot system is im-mune to the single point of failure that may occur in the latter systems. The distributed solution is inherently redundant [8].
Distributed action
Multiple robots can be in many places at the same time and they can work on different tasks [9].
Parallelism
Many robots can work simultaneously and cooperatively to accomplish a task [7].
Complexity
Complexity affects the cost of the system and the complexity can be reduced since de-signing and constructing multiple simpler robots compared to designing and constructing a single robot system is easier. Many environments or missions may require a mixture of robotic capabilities that is too extensive to implement into one single robot [7]. Often each agent in a team of robots can be simpler than a more comprehensive single robot solution [9].
Performance
Team members can exchange sensor information, help each other to scale obstacles and collaborate to manipulate heavy objects. A single robot system does not have these capabilities [10].
Divide and Conquer
A large number of human solutions to real world problems use multiple humans sup-porting and complementing each other. These tasks are inherently distributed in space, time or functionality and require a distributed solution [7]. Certain problems are well suited for decomposition and allocation among many robots [9].
Task completion time
Many robots can accomplish the mission faster than a single robot can (this can only be applied to tasks that can be divided into subtasks that can be executed in parallel.
Human lives
Using a DMR system instead of humans removes humans from danger. Many of the target applications of DMR systems are potentially hazardous to humans. Introducing robots correctly can improve the quality of life by freeing workers from dirty, boring, dangerous and heavy labour [W3],[12].

Disadvantages

Coordination and cooperation can be hard to achieve. Single robot systems don’t have these prob-lems.
Having multiple robots in a limited area introduces the problem of interference and collisions.
Controlling multi-robot systems are harder than controlling single robot systems.
Testing multi-robot systems ought to be harder than single robot systems because in single robot systems the robot only needs to be tested with its surrounding environment but in multi-robot sys-tems the robots needs to be tested in the environment in the presence of the other robots.

Current and future DMR applications

The literature used in this survey shows many application areas for DMR systems. Some of these are presented here. These applications are well suited for team-based approaches. Some of these applic a-tion areas are potentially dangerous tasks for humans. These applications areas represent extreme envi-ronments (except industrial and household applications) where the environment might change any time during the mission affecting the robots sensors and ability to function. It is not easy to make one almost flawless robot that would function in these environments and if it breaks the mission would fail. Sending many robots increases the chance of mission success. Robots are suited for applic ations that involve one of the three D’s (dirty, dull or dangerous).

Current DMR applications

These are some of the current DMR applications that exist in research and industry today. Re-searchers have certain domains they use to experiment their theories on:

Test domains

Test domains are applications that researchers use to test their algorithms, architec-tures and robots on. The test domains used are box pushing, trash can collecting, cleaning, keeping formation, hazardous waste cleanup, cooperative observation of multiple moving targets and robot soccer.

Robot soccer

Robot soccer is played in different ways. Balch [13] utilizes the following rules. Teams are composed of four players. The sidelines are walls (no out-of-bounds). The goal spans the width of the field’s boundary. The gameplay is continuous. In Ro-boCup there are different classes with partly different rules.

Cleaning

Robots are used for decontamination and decommissioning of legacy manufacturing facilities and hazardous waste cleanup. They can also be part of a nuclear accident re-sponse. In a real world application today robots are used for surveillance and charac-terization prior to and during clean up activities of radiologically contaminated areas instead of exposing a radiation control technician. In Anderson’s [14] report we can see how MACS (Mobile Automated Characterization System), RACS (Reduced Ac-cess Characterization Subsystem) and TRACS (Transmitter for Reduced Access Characterization Subsystem) cooperate to accomplish the cleaning task. MACS de-ploys RACS for areas that is non accessible by a large floor characterization system. TRACS works as a repeater to improve the radio communication between RACS and MACS.
There exist robotic vacuum cleaners but these are single robot systems.

Robot wars

Robots are used in various military operations, either as weapons, as surveillance equipment where multiple robots cooperate and perform tasks such as target recogni-tion, dynamic target tracking, terrain recognition, and autoconfiguration to maximize field coverage. There is also a TV-show called “Robot Wars” where robots are put into a battle zone to destroy each other. These robots, however, are teleoperated and not autonomous.

Medical and personal care

Robots can perform surgery and they could be created so that they don’t suffer from communication misunderstandings between the actors in the surgery. Robots can also be designed and manufactured so that they are more accurate and precise than humans [15]. It is uncertain if the surgery application is a DMR application or not. If model-ling it to resemblance human action there certainly will be more than one robot help-ing to make the surgery as efficient as possible.

Security

The company Cybermotion has placed more than 80 guard robots (1998) to its cus-tomers where they monitor facilities for fire [16]. The guard robots can be fitted with a camera, optical flame detector, microwave intrusion radar, smoke, humidity, gas and temperature sensor. It is uncertain if their security robots cooperate in their tasks but surely they can be fitted and programmed to do so. Related areas to security are sur-veillance and reconnaissance.

Household and industrial maintenance

There exist both auto lawn mowers and vacuum cleaners that do these duties for you. Other areas are painting, assembling, pressing, welding, handling, sorting, finishing and gluing. It is uncertain if it exists DMR applications in these areas today.

Entertainment

Entertainment is also an area suited for DMR systems. One example is the advanced Sony AIBO robot dog that is programmable. Another not so advanced example is the annoying toy Furby that can chat with its Furby friends.

Future DMR applications

“What is considered fiction today might be the facts of tomorrow.”
Victor Adolfsson
Apicella [17] believes that it is not necessity that is the mother of invention. Instead it is laziness, to reduce manual or intellectual work or to extend human ability. Today’s robots are well suited to repetitive or remotely controlled tasks in manufacturing, medicine, industrial research, and other areas, but autonomous and freely mobile robots will require 10 to 20 more years of technology advances.
Future technologies that are believed to impact robotics are pattern recognition, speech recognition, natural language processing and synthetic characters [17].
Hans Moravec at Carnegie Mellon University presents this timeline for robot intelligence.
Year: 2010,Processing power: 3,000 MIPS, Intelligence equivalent: lizard
Year: 2020, Processing power: 100,000 MIPS, Intelligence equivalent: mouse
Year: 2030, Processing power: 3,000,000 MIPS, Intelligence equivalent: monkey
Year:2040, Processing power: 100,000,000 MIPS, Intelligence equivalent: human
According to his timeline it takes 40 years until we can create robots with the intelligence equivalent to humans. It is not only processing power (the hardware) that will make robots smarter. I believe that the software of the robots must be better than today for his timeline to be true. Within twenty, thirty years, household robots will be sold to a price about the same as for cars. These robots aren’t specia l-ized; instead they learn how to do a job (this according to the Daily News (Dagens Nyheter)) [15].

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The Borg from Star Trek.

“The Borg is an immensely powerful race of humanoids from the Delta Quadrant. Strengthened with cybernetic implants, Borg awareness is as a collective. Individual thought is considered primal and should be « assimilated » into the collective. All Borg are equipped with cybernetic hardware. Different devices are given to different Borg to assist in the specific task they work at. Each Borg is part of a giant subspace communications network, called the Borg Colle ctive.” From http://www.ucip.org/divisions/borg/
Although fiction, it does raise several interest-ing DMR topics. The Borg collective is the way they communicate and it is used for sharing information. Each Borg is a distributed sensor, as well as an actuator that can affect the environment. They assimilate the behaviours of the one they come in contact with and hence learn from them. They are modular (can attach different devices to them) and they are specialized for a certain tasks hence they are heteregenous team.
In the future, robots will probably have and use polymorphic capabilities and shift shapes in order to complete missions like Transformers [18]. This requires good building blocks and a proper design when creating the robots in the first place. The ability to shift shape will allow the robot system to scale obstacles and move over unstructured terrain according to Ünsual [19].

Save human lives

Robots will take care of those jobs that are dangerous for humans. There exist both military and civilian applications where robots can take care of dangerous jobs. Robot teams can be created that have higher performance than its human counterpart accord-ing to Ericksson [4].
Robots are ideal for fire fighting because they can be designed to withstand heat and be of low weight and hence can help to locate survivors in a burning building without jeopardizing the human fire fighters.
Arkin [9] describes robotic scout teams that will be able to perform better than a hu-man scout team thus removing humans from possible danger. These could be operated in sea, on ground, in air and also in space.
Robots can also be used for security and monitoring presence and communications in-frastructure according to Thayer [12].
“Over 200 miners is believed to have died in a flooding accident in a tin mine in China” (from Aftonbladet 31 July 2001). Mining is a dangerous job for humans and it is suggested that robots do this job in the future [15].
Small robots are well suited for mine sweeping, nuclear power plant maintenance work and military applications, where the environment is unsafe for humans, and the risk factor is too high to utilize expensive, highly specialized robots. This is according to Evans [20].
Robots could be dispersed in an area that suffers from some sort of environmental dis-aster or fire and find survivors faster than ordinary search and rescue teams containing humans, dogs and heat cameras [W4].
DMR systems could be used in war situations to gain information advantages over an enemy allowing its weapons to be deployed more efficient.
Many (or all) researchers believe that DMR systems will do these dangerous tasks for us.

Site preparation on Mars

Robot systems are expected to be used in different space applications. Robots operat-ing in space really need to be autonomous since it is hard to teleoperate over vast dis-tances because of the time delay. Ericksson [4] writes that supervised intelligent sys-tems (supervised autonomous robotic systems) will enable space exploration.
One of the applications suitable for robots is site preparation task on Mars (and other planets). There they will prepare the infrastructure. This kind of application requires path planning and control of mobile robots in rough terrain environments. Teams of robots are required to work together to physically alter outdoor terrains, levelling the soil and transporting and deploying PV (photovoltaic) tent arrays. The site preparation task is described by Guo [21].
On other planets there is still the need to control the robot team to ensure that they co-operate efficient in highly unpredictable and uncertain environments.
To build robot teams that survive in these harsh environments, the architecture must allow robots to opportunistically select actions based upon the variety of dynamic changes they may experience. Some of those actions could be cooperative clearing and to recruit help when needed.
Teleoperation is necessary in order for the human controller to select certain tasks that need to be prioritised by the robots or to prohibit them from executing a particular task. Robot team members should also be constructed so that they will suggest new activities based on information that they have gathered and the human controller might have missed.
After the site has been prepared and when humans have arrived at the site the robots are needed for maintenance work on the site.

Table of contents :

1. INTRODUCTION
1.1 PURPOSE AND GOALS
1.2 SCOPE
1.3 METHOD
1.4 THESIS OUTLINE
2. BACKGROUND
2.1 DEFINITION OF DISTRIBUTED, MOBILE AND ROBOTICS
2.1.1 Definition of “distributed”
2.1.2 Definition of “mobile”
2.1.3 Definition of “robotics”
2.2 RELATED DEFINITIONS
2.2.1 Intelligent robot
2.2.2 Definition of “self -contained”
2.2.3 Classification of intelligent robotic systems
2.2.4 Definition of an agent
2.3 MY DEFINITION OF DMR
2.4 HISTORY
3. WHY USE A DMR SYSTEM?
3.1 ADVANTAGES
3.2 DISADVANTAGES
4. CURRENT AND FUTURE DMR APPLICATIONS
4.1 CURRENT DMR APPLICATIONS
4.1.1 Test domains
4.1.2 Robot soccer
4.1.3 Cleaning
4.1.4 Robot wars
4.1.5 Medical and personal care
4.1.6 Security
4.1.7 Household and industrial maintenance
4.1.8 Entertainment
4.2 FUTURE DMR APPLICATIONS
4.2.1 The Borg from Star Trek
4.2.2 Save human lives
4.2.3 Site preparation on Mars
4.2.4 Exploration
5. STATE OF THE ART
5.1 CHARACTERIZATION OF A DMR SYSTEM
5.2 COMMUNICATION
5.3 ARCHITECTURE
5.4 CENTRALIZED OR DECENTRALIZED APPROACH
5.5 DEADLOCK
5.6 COOPERATION
5.7 LEARNING
5.8 RECONFIGURATION
5.9 NAVIGATION / EXPLORATION / RECONNAISSANCE
5.10 FORMATIONS
5.11 MULTI-TARGET OBSERVATION
5.12 TASK ALLOCATION
5.13 TRANSPORTATION
5.14 BIOLOGY
5.15 SYNTHESIS OF ROBOT TEAMS
5.16 TRAFFIC TELEMATICS
6. CONCLUSION
6.1 GUIDELINES
6.2 BIT RESOURCES FOR DMR RESEARCH
6.3 OPEN RESEARCH QUESTIONS
6.3.1 Communication
6.3.2 Learning
6.3.3 Architecture
6.3.4 Team size
6.3.5 Control
6.3.6 Reconfiguration
6.3.7 Performance
6.3.8 Other
6.4 FUTURE WORK
6.5 SUMMARY
7. REFERENCES
7.1 REPORTS AND ARTICLES
7.2 WEBREFERENCES
APPENDIX I. DMR RESEARCH LABORATORIES
ACADEMIA
North America
Europe
Asia
GOVERNMENT
Swedish Defence Research Institute (FOI)
DARPA
NASA Jet Propulsion Laboratory (JPL)
Center for Engineering Systems Advanced Research, Oak Ridge National Laboratory (ORNL) 46
APPENDIX II. DMR COMPANIES
Sony
Irobot corporation
Activmedia robots
Cybermotion
Denning
K-Team
Lego Mindstorm
Honda
Electrolux
Husqvarna
ABB Robotics
SAAB
Nomadic
APPENDIX III. DMR ORGANISATIONS
International Federation of Robotics (IFR)
National Science Foundation (NSF), Robotic council
Swedish Industrial Robot Association (SWIRA),
RoboCup Federation
International Federation of Automatic Control (IFAC)
European Robotics Research Network (EURON)
IEEE Robotics and Automation Society
APPENDIX IV. DMR JOURNALS AND CONFERENCES
JOURNALS
CONFERENCES
APPENDIX V. TERMS AND ABBREVIATIONS

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