Game Theory based Path planning for Multi-agent system

7/27/2019 Game Theory based Path planning for Multi-agent system

1/24

1

Cooperation and Competition in Multi -Agent Systems (MAS)

National Institute of Technology, Durgapur

Mechanical Engineering Department

Submitted by:

Debal Saha (08/ME/76)

Aman Agarwal (08/ME/83)

Nishant Kumar Singh (08/ME/93)

Manjunath Shrivastav Gandham (08/ME/78)

Madhyama Thakur (08/ME/60)


2/24

2

Contents

Acknowledgement ... 3 Abstract ............. . .. . 4

I. Introduction ... .... .. . 5

II. Literature Revie w .. .... 6

III. Game Theory for MAS .. ... 7

IV. Collision avoidance scheme for MAS ................ 8

V. Strategies for soccer robot ... 10

VI. Experimental Set up ... .................. ..... 12

VII.Technical Difficulties faced .. ... 18

VIII. Probable reasons non-functionality of microbots ................................ 20

IX. Remedies .. 22

X. References ..... . ... 24


3/24

3

Acknowledgement

It is a well-established fact, that any endeavour undertaken is the amalgamation of thedirect or indirect efforts of countless individuals coming together for a common goal. Aswe present our report on our final year project, we take this opportunity to express oursincere gratitude to all those who rendered valuable support to our project.

First and foremost, we are thankful to our Project Guide Dr. Nirmal Baran Hui forallowing us to carry out our final project under his able guidance. The discussionregarding the various important aspects of the project, the clarification of some

complicated topics, and the provisions of experimental set up by him to our project group were very crucial for the accomplishment of the project. He not only guided us tothe best possible means of accomplishing a said goal, but also allowed us to explore ourrealms and make mistakes, and to learn from those mistakes. We are greatly indebted tohim for the trust he showed on us and the latitude he allowed us.

Further, we must acknowledge our entire Department of Mechanical Engineering forproviding us with state of the art equipment and experimental setup.


4/24

4

Abstract

The report encapsulates both the theoretical foundation and the associated experimental setuprequired for studying and analysing the developed theoretical work. The objective of our

project was to develop a game theoretic approach to address the issue of competition andcoordination in Multi-Agent Systems (MAS). Here it has been shown how we can model thesame real-time problems marked by dynamic constraints in the form of games where the

participating agents can be treated as players with the combination of their available moves asstrategies. The developed approach has been implemented for devising motion planners for agents of a MAS responsible for collision-free traversal of randomly generated paths. Asecond analysis is done on strategies employed by soccer robots using the game theoreticapproach for MAS. The theory is developed keeping in mind its practical feasibility and itscredibility to embody the basic principles of MAS. The experimental set up described in thereport is the MIROSOT microbot package mainly utilized in robo-soccer tournaments. It is anefficient test bed to analyse theories of MAS. In the last two sections the various technicaldifficulties faced during carrying out the experiments are enumerated. Some remedies arealso suggested so that the work can be continued further.


5/24

5

I. Introduction

Since the inception of the concept of Multi-Agent Systems (MAS) there has been a significant shift invarious realms from the idea of centralized control to the approach of distributed control. The changesin the control strategies adopted for soccer robots, the change in the way to obtain optimal schedulingand resource allocation in shop floor control, the efficient routing of information/data incommunication networks are few illustrations where the concepts of MAS has much better results ascompared to that of the conventional centralized approaches.

Various algorithms and approaches have been suggested for solving various problems by consideringthem and a system comprising of various agents. A strong proof regarding Genetic algorithmoptimized Fuzzy logic controllers and Genetic Algorithm optimized Neural network based controllersoutperforming Potential field method based controllers, were obtained in a paper published by Hui

N.B.,Pratihar D.K. , A comparative study on Some Navigation Schemes of a Real Robottackling moving Obstacles . The reason is given as the absence of any optimization technique in the

Potential field method based approach or algorithm. This paper that forms the backbone or starting point of our project has considered a single planning robot. However, our main emphasis is onmultiple robots working in a common dynamic environment (like a soccer game environment).

One such approach is game theory. In this paper this approach is used to work with MAS. Gametheory is a method of studying strategic decision making. Game theory applies to a wide range of class relations, and has developed into an umbrella term for the logical side of science, to include bothhuman and non-humans, like computers. Classic uses include a sense of balance in numerous games,where each person has found or developed a tactic that cannot successfully better his results, given theother approach. The games studied in game theory are well-defined mathematical objects.

At first, a brief review of the significant work done regarding various aspects of MAS and their implementation in diverse realms has been explored. Then the relevant concepts of game theory arediscussed.

Some analogies are made between the scenarios that will be tackled in the subsequent sections andthe aspects of game theory resembling them. Two realistic problems are discussed using the GameTheoretic approach for MAS which are: 1) collision avoidance in MAS and 2) Strategies for soccer robots. How a collision is defined in the soccer robotics arena is defined and various schemes aretried to avoid the same. Terms such as cooperation and coordination gain enormous significanceand form an integral part of our project.

Later some conclusions are drawn from the analysis presented in the paper. Some suggestions are alsomade regarding the scope for betterment.
http://en.wikipedia.org/wiki/Decision_makinghttp://en.wikipedia.org/wiki/Umbrella_termhttp://en.wikipedia.org/wiki/Umbrella_termhttp://en.wikipedia.org/wiki/Decision_making


6/24

6

II. Literature Review

Cooperation and coordination are two important traits that all researchers try to incorporate in MAS asthese two phenomena are central to the successful application of MAS for arriving at tangiblesolutions to the dynamic problems. These traits are incorporated in MAS by providing means of communication between agents and employing mechanisms to arrive at a consensus for the wholesystem of agents after the negotiation on the strategies employed by each agent. Various researchershave propos ed various ways to formally define the term coordination and cooperation among the

participating agents in a problem solving scenario. In [4] Jmaiel et al has proposed a formal model todefine the coordination structure in a MAS with a formal operational semantics based on settheoretical language for the coordination process among agents. In [6] Prunak et al has describedvarious terminologies used for the MAS both for its individual agents as well as for the system as awhole. The various attributes of MAS like coordination, cooperation, collaboration etc. have beencollectively denoted as Co-X and have been studied in the generalized context to assign the variousconstituents of Co-X either to an agent individualistically or toe the whole MAS holistically. Thisassignment was done based on both empirical and statistical analysis of various processes prevailingin MAS implementation. For example the Joint information of agents is regarded as correlationentropy and by statistically computing this entropy the degree of correlation can be established.

The primary issue to be addresses in such MAS is to devise an efficient way to create subtasks thathas to be assignment to individual agent so that the agents should try to arrive at a consensus whiletrying to complete the assigned subtask. Many researchers have rigorously studied the issues of cooperation and coordination while seeking consensus for the MAS. In [10] Qianwei et al havestudied the issue of collision avoidance in MAS by using centralized control mode for avoiding staticobstacles. But it does not take in consideration the dynamic nature of the surrounding. In [5] Vishnu et

al has explained that by implementing single agent path-planners the complexity of tackling variousissues arising from the dynamic nature of surrounding/environment. They have developed adecentralized multi-agent rapidly exploring random tree (DMA-RRT). By having prior information of some obstacles a path is planned by a component of DMA-RRT algorithm whereas another component keeps updating this path following strategy dynamically by communicating with other agents and following a Merit-based Token Passing Coordination Strategy. Thus their thesis is moreefficient and realistic in comparison to the centralized approach mentioned in [10].

But seldom has the issue of competition among agents with different attitudes been explored. Someresearchers have tried to incorporate the concept of completion among agents by employing biddingmechanisms e.g. [1]. In [1] the authors have tried to address the problem of optimum scheduling of and resource allocation for the various processes in a production plant by implementing the conceptsof Game theory and the Multi-agent systems. The various processes involved in the production of

plant are treated as individual agents. A hetrarchical Multiagent system (where there is no predefinedmaster-slave relationship) has been considered opposed to the hierarchical system where there is

predefined master-slave relation among agents. In the hetrarchical system the negotiations taking place between all the agents in a distributed fashion. The negotiation among them is term co-opetition(= cooperation + competition)has been used to refer to the interaction between the various processesof the production plant. The allocation of resources and the issue of scheduling have been doneoptimally by treating the processes a normal form game. The time required by each particular processis referred as the available strategies for the processes which are the players.


7/24

7

III. Game Theory FOR MAS :

In this section the concept of game theory is explained along with the description of the analogiesrequired for implementing these concepts in MAS. A game can be defined as a decision-makingscenario where one or more participants are involved and their decisions are interdependent. Every

participant has to decide on the strategy he/she has to adopt. The participants can be called players of the game. The outcome of a game is decided by a comparative study of the various combinations of strategies for each player and the possible outcomes or payoffs of these possible combinations. Wecan consider a two players (A and B) game where each player plays with one strategy at a time (S A and S B). If by adopting a particular strategy S A1 player A gains more than by adopting another strategy S A2 irrespective of any strategy S B adopted by Player B , then S A1 is said to be dominant over Strategy S A2.

Nash Equilibrium

The behaviour of the interacting agents can be interpreted in terms of Nash Equilibrium and the globalsystem performance correlates to the payoff of this equilibrium. The move of the agents (strategyadopted by agents) will be decided based on the dominant strategy i.e. the strategy which maximizesthe payoff. In most of the cases one or more Nash Equilibria may emerge from the confrontation of strategies, leading to a pure strategy , if Nash Equilibria is unique or mixed strategies in case of multiple equilibria, which may be probability driven.

Pareto optimal solution

A particular case which illustrates the efficiency of cooperation is obtained when a Pareto Optimumexists. In that case, using a Pareto Optimal strategy in a repeated game scenario is expected to provideoptimal results. In a two-player game this cooperation strategy is referred to as the well-knownPrisoner s Dilemma.


8/24

8

IV. Collision Avoidance Schemes for MAS

A very simple and effective way to test the developed game theoretic approach to address the issue of completion and cooperation in MAS is the development of motion planner for a MAS with individualagent having different priority and attitude. Random starting points and destinations can be generatedfor each agent. The motion planner should be responsible for generating a path between the starting

point and the destinations of the agents and ensuring their collision free traversal on that path. Herewe define conflict scenario as the situation in which the paths generated for two particular agents bythe motion planner to reach their respective destinations intersect or so close that they may lead tocollision of the agents. For the study of such scenarios the motion of entire MAS is tracked for thetime period in which the agents start moving and finally reach their respective destinations. Thiswhole time period is then divided in discrete time intervals during which the position of each agentand its future motion is checked for detecting any impending collision or in other words any conflict

scenarios .

While checking the movements of an agent in a particular time step, there may be more than oneagent which can impose a threat of a future collision with the agent under consideration. To generatea collision free for a particular agent, it will be paired with every other agent that impose the threat of collision in the near future and the collision between the agents constituting each such pair will beconsidered as separate conflict scenarios. By resolution of each such conflict scenario the further motion of all the agents will be planned for the next time step. After execution of the planned motionin the next time step, again the agents which can collide in the then next time step will be consideredand for each agent pairs will be formed for studying the conflict scenarios. Thus resolution of conflictscenarios in consecutive time steps will eventually help all the agents reach their respectivedestinations without colliding with each other.

We can consider a very simple game for a conflict scenario of an impending collision between twoagents considering them to be the payers of that game. Each player of the pair which are playing thegame for the resolution of the conflict scenario (impending collision) has just two moves as options,one is to stop other is to move. Let, P1 and P2 be the two players. Now pIJ will represent the payoff for the I th player when he adopts J thStrategy. For example p12 represents the payoff when Player P1has adopted 2 nd strategy.

P2P1

Stop Move

Stop ( p11, p21 ) ( p11, p22)Move ( p12, p21) ( p12, p22 )

Fig. 1. The payoff matrix of a normal form game between two players

The payoff pIJ for each player for adopting a particular strategy should be determined by a particular payoff function. Each of the available strategies ( s i i.e. stop, move) should contribute to the payoff.Thus we can define payoff function as a function of the available strategies and the certaincoefficients relating to the cooperative and non-cooperative aspects of the agents so that by tuningthese coefficients (adjusting their values) we can obtain such payoffs ( pIJ ) for the players (involved inthe game representing a conflict scenario) which will help determine conclusive strategies. Now, wecan write:


9/24

9

pIJ = f (C co, C nco, Ps J) where

pIJ = Payoff for I th player if it chooses to adopt J th strategy

Cco = Coefficient of Cooperation

Cnco = Coefficient of Non-cooperation

Ps J = A value characteristic to the strategy s J (like if the Jth strategy i.e. s J is to stop then Ps J may be

the time for which the Player stops)

The above game can also be treated as a zero sum game. In a zero game between two players, one player s gain is the other player s loss in terms of payoff and each cell of the payoff matrix for thezero game will have a single entry. In our case, if we represent the conflict scenario as a zero sumgame then the payoff of one player will be negative of the other. In such a case we can come out witha payoff function for calculating the payoff of a scenario (the combination of the strategies of both the

players) instead of calculating the payoff for individual players for their respective strategies. Here pIJ will mean the payoff for the scenario where the 1 st player (P1) adopts I th strategy and the 2 nd player adopts J thstrategy. If we consider stop to be th e 1 st strategy and move to be the second strategy,then the payoff table will look like as follows.

P2P1

Stop Move

Stop p11 p12Move p21 p22

Fig. 2. The payoff matrix of a Zero Sum game between two players

The payoff function for the zero-sum game will have the same factors as that for the normal formgame as discussed earlier with the variation that instead of having a factor representing thecharacteristic value of one strategy, there will be two factors, one representing the characteristic valueof the strategy adopted by player P1 and another for that of the strategy adopted by the player P2.

pIJ = f (C co, C nco, Ps J, Ps I) where

Ps J = Characteristic value for the J th strategy adopted by player P1

Ps I = Characteristic value for the Ith strategy adopted by player P2


10/24

10

V. Strategies for Soccer Robots

Soccer robotics has proven to one of the ideal test beds to test/simulate the effectiveness of developedstrategies and concepts for the MAS. Not only does it require cooperation among the members of thesame team for winning the game but also requires to take the issue of competition among the agentsso that the need for adequate dribbling and passing of ball by and among the agents, respectively can

be solved to increase the possession of the ball and thus trying to score more goals in the game.

The strategies of soccer robots are dependent on both the responsibilities/role assigned to them andalso on the region in which they are currently located. The whole field/arena for the soccer game can

be divided in two regions viz. the home ground and the opponent s ground. The players arecategorized into defenders, mid fielders and strikers. Generally, the purpose of a player in homeground is to defend the ball from going towards its own goal. Similarly when in the opponent s

ground, a player will try to take the ball towards the opponent s goal and score a goal. While a striker is given the responsibility to score goals by maintaining a position in the opponent s ground, adefender is given the responsibility defend its own goal by clearing the ball out of regions in the homeground which are vulnerable and from where an opponent team s player can score goals.

Fig 3.Microbot used for experiments in [9]

Scoring of goals, defending goal all suchactions can be done by just two basicmoves/actions which are dribbling the

ball/holding the ball and passing the ball . If we consider a microbot as shown in the pictureabove, then the basic actions of dribbling and

passing of ball will further get reduced to twoactions of stop and move only. Passing a

ball can be done by moving with the ball in thedesired direction and stopping and allowingthe ball to roll further and reach the desired

player. Dribbling can be thought to be done bysimply moving with the ball. The same moveand stop actions can be adopted by the other

player who has the responsibility of receiving

a pass. It can move towards the incoming balland stop to receive it. Now the issue arising insuch a scenario is to decide when to pass the

ball and when to retain it. Various factors thatwill constraint the decision-making process for a player can be:

1) position of the ball2) its own position (whether it is in

opponent s ground or in home ground) 3) the position of opponents (is there any

opponent nearby)4) the position of other teammates to

check the feasibility of a pass5) its own role in its team (is it a

defender or a striker)6) distance from the goal (from both the

opponent s as well as own goal)

The position of the players should be known to all others (as it is in the real soccer game) and it is oneof the crucial factors affecting the choice of a strategy or to decide upon a particular strategy. The

players in immediate vicinity (defined in terms of range of vision of agents) include opponents which


11/24

11

are more susceptible to tackle as well as teammates who can take a pass easily. A player if presentnear own goal will have more tendency to pass it off rather than a player which is near opponent sgoal. But the passing of a ball also depends on the presence of a team mate with in the range of

passing of the ball for a player. The decision-making scenario can be represented as a normal formgame. The game will be between two players of the same team which are nearest to each other. Let usdenote them by P1 and P2. The game representing the scenario is one which will decide how a player and its nearest teammate interact with each other. The normal form game will lead a payoff matrixsimilar to that shown in Fig.2. For this all the factors enumerated above need to be consideredseparately and should be part of the payoff function which will decide each player s payoff ( pIJ ).

pIJ = f (C com, C coop , C 1, C 2, C 3, C 4, C 5) where

Ccom = Coefficient represent tendency to compete

Ccoop = Coefficient representing tendency to cooperate

C i= Coefficient with the characteristic value for the ith

factor enumerated above and i = 1,2..5.Here the coefficient for competition and cooperation are quite useful. Their significance can beillustrated by a particular scenario concerning player P1 of a game. Let us check the five factors thatwe enumerated previously which can affect the decision making process. The first factor is about the

ball s position and we can assume that P1 possesses the ba ll. Next we can consider that position of P1is in its own ground. Let P2 be its nearest teammate. There are neither any opponents nor any other teammate as near as P2. P1 is a defender and is very near to its own goal. The distance between P1and P2 may close enough for an efficient pass. This may appear to be an ideal situation for P1 to passthe ball. SO it may adopt to move for a time step and stop for the next time step in a way to pass it toP2. But in this process there may be an opponent who may not be near in previous time steps but isnear now and can intercept the ball and score goal as P1 itself is near its own goal. So here we need toconsider about other options. An option may be tuning the coefficient of competition i.e. C com of P1to higher values so that it does not pass the ball though it appears as if the conditions are so muchfavourable for a pass. By having a higher value for C com , P1 will have more tendency to keep the

ball with itself rather than letting it go. An exactly opposite situation may arrive when P1 is striker, isnear opponent s goal, has no one nearby and may choose to shoot. But the passing of the ball to other teammate which though may not be near but is positioned in a direction where a clear shoot at thegoal is possible and is more likely to get the ball into the goal, may be the more logical option. Heretuning the coefficient of cooperation i.e. C coop may help P1 to decide in more logical way rather thandeciding on the basis of favourable conditions.

The value s for these coefficients C com and C coop , can be decided by heuristic functions which can be formulated after running some simulated games and seeking for the best values that help the players to decide more logically.


12/24

12

VI. Experimental Setup

The Experimental Set Up can be divided into 3 distinct heads i.e MyVision Board RF Board CCD Cameras

All of these heads need to be first installed and then tested if they are functioning properly or not.A brief outline is provided here enumerating how to install and check these hardware components.

1. Installation of MyVision board:

The MyVision Board needs to be inserted in the PCI slot of the computer. It acts as an interface for the interaction between the CCD camera and the computer. The captured images by the CCD cameraare transferred to the computer via the BNC cable that attached the CCD camera to the MyVision

board. The drivers are installed from the CD provided by the manufacturers of the mirosot package.

2. RF Board:

RF board allows the computer to wireless communicate with soccer robots. RF board is installed tocontrol and move the soccer robots through wireless communication. This is done by connectingthe serial cable into JP2 of the RF board and a serial port (COM1) of the PC. Then we plug the

power adapter (DC9V) into J1 of the RF board and AC power source (AC220V).


13/24

13

* The three pins of JP4 should not be jumped with each other. That is, JP4 should remain open.

JP4 ANT BIM418(or 433) DC 9V JP1 POWER DC 5V JP7

Radiometrix Module:

A RF (Radio Frequency) module is a compact component used for wireless radio communication.In this case, radio frequency refers to a general electric wave and not only a radio broadcastingfrequency. RF modules can be classified by frequency, modulation method, data, output strength, etc.RF modules are frequently used when precise wireless applications are necessary.

BiM-UHF

The BiM-418-F and BiM-433-F are miniature UHF radio modules capable of half duplex datatransmissions at speeds up to 40 Kbit/s over distances of 30 meters in-building and 120 meters


14/24

14

over open ground. Single 4.5V to 5.5V power supply is required.

TX2, RX2

The TX2 and RX2 data link modules are a miniature PCB mounting UHF radio transmitter andreceiver pair which enable the simple implementation of a data link at up to 40 Kbit/s at distancesup to 75 meters in-building and 300 meters open ground. 3.3V and 5V version are available.

Frequency Speed SpeedDistance RadiatedPower ReceiveSensitivity Power

Whip Antenna

TX2418.00 MHz433.92 MHz 40K bps

75~300 m -6 dBm+9 dBm 4.0~6.0 V

16.5 cm15.5 cm

RX2 418.00 MHz433.92 MHz 40K bps 75~300 m -100 dBm 4.0~6.0 V 16.5 cm

15.5 cm

Tx Module

Frequency Speed Distance RadiatedPower

ReceiveSensitivity

Power WhipAntenna

BiM-418-F

418.00MHz

40K bps 30~120 m -6 dBm -107 dBm 4.5~5.5 V 16.5 cm

BiM-433-F

433.92MHz

40K bps 30~120 m -6 dBm -107 dBm 4.5~5.5 V 15.5 cm


15/24

15

Rx Module

An RF Transmitter Module:-


16/24

16

Power supply

The board uses a single DC 5V power source. Power can be supplied via threemethods:

DC 5V to the JP7 port. 9V battery to the JP1 port. DC 6~12V adapter to the J1 port.

You must use only one of the above. If a DC adapter is used, and the LED D2 does not light,change the polarity of the plug. The Charisma board has a power cut-off diode, which preventsdamage due to incorrect polarity.

Power Port

5 V JP7

6~12V adapter J1

9V battery JP1

Fig 3: Radiometrix module- BiM-UHF transceiver


17/24

17

3. How to install CCD camera

The CCD cameras are set up after this. The Lens is mounted on the CCD camera and we plug theLens Cable (Auto Iris Control Cable) into the camera connector on the right side of the CCDcamera. Set the Dip Switch (Lens Selection Switch) on the right side of the CCD camera to DC.That is why the lens is controlled by DC. Connect the Camera Power Adapter (AC24V) to the 2

pin connector on the rear of the CCD camera.Finally the CCD camera is fixed to the CameraStand. The height and position of the camera is adjusted according to requirement.The VideoCable (included in MyVision Board Pack) is connected to the CCD camera and the MyVision

board.


18/24

18

VII. Technical Difficulties Faced

Incompatibility of the software Mirosot to Windows 7/Vista/XP:-

Fig 1. DB9 cable

Our experiment has to be carried out with the help of a software named Mirosot which wasto be used for the manipulation of the soccer robots. However, the problem that we faced wasits incompatibility to various operating systems like Windows 7/Vista/XP. After installing thesoftware we tried testing it but couldn t get any results, may be the software was not able totransfer the required signal to the RF Transmitter through DB 9 cable (Fig 1). Later on we hadto install window 2000 as it was mentioned in the specification of the setup, still we wereunable to get the results due to some other reasons.

Fig 2: Software used to run mirosot robot


19/24

19

Difficulties faced while charging the battery of the bots:-

Another problem that we faced during testing was improper charging of the bots. Thespecifications provided to us in the manual for the proper charging of the bots at differentmodes were-

Fast Mode:

Time required for full charging of the bots is 6 hrs.

Slow Mode:

Time required for full charging of the bots is 12 hrs.

Charger used for charging the Mirosot Robots:-

RS-BATTERY-Charger

Battery charger kit for the RS-BATTERY-NiMH-450, RS-BATTREY-NiMH-600, and RS- BATTERY-NiCd batteries.

Specifications

Size: 35 x 35 x 16 mm

Power: 7.2 V (1.2 x 6), 450mAh

7.2 V (1.2 x 6), 600mAh

Features:

Designed for a small robot. Compact and high power density

However, the backup given by the bots after full charging always lasted for 5 minutes atmax, and some of them even had zero backup. Therefore, thesufficient time required to carry out the experiment was not fulfilled.

RF Transmitter: Problem with the transmitter:-

However, the problems that we encountered during the test was that the pins showed novoltage variation which was necessary for transmission. As mentioned in the abovedescriptions, the voltage and the current readings that were recorded at each pins were moreor less the same. The supply voltage normally found was around 5.0 V, the voltage reading atthe RX and the TX terminals were found to be 1.5 and 0.5 V and for the transmission of the

signal this voltage must show some variations, but there was no sign of variation in either of the pins .


20/24

20

VIII. The probable reasons for the non-functionality ofthe microrobots:

Software incompatibility :

Software incompatibility is the foremost problem to be looked upon in carrying out the testingoperations. There may be an error in the software itself. The software is designed at a veryearly stage before introduction of latest windows operating systems(Windows XP/Vista/7). Sothe software may not have been updated to run or the improper addressing of its compatibilityissues. This may lead to severe incompatibility issues. Hence this issue is to be addressed

primarily before proceeding any further into the testing operations.

Error due to serial port :

The error in the serial port of the computer may be due to hardware incompatibility with theRF Transmitter or there may be error in the baud rate for data transmission. As explained in[1] the name "serial" comes from the fact that a serial port "serializes" data. That is, it takes a

byte of data and transmits the 8 bits in the byte one at a time. The advantage is that a serial port needs only one wire to transmit the 8 bits (while a parallel port needs 8). Thedisadvantage is that it takes 8 times longer to transmit the data than it would if there were 8wires. Serial ports lower cable costs and make cables smaller.

Before each byte of data, a serial port sends a start bit, which is a single bit with a value of 0.After each byte of data, it sends a stop bit to signal that the byte is complete. It may also senda parity bit.

Serial ports, also called communication (COM) ports, are bi-directional. Bi-directionalcommunication allows each device to receive data as well as transmit it.

The baud rate is the rate which is used for the communication purpose and it is used toidentify that how much of the data had been transferred but at how much speed. This is thesymbol which is used for the measurement of the symbols but at the rate of per second. Thisis used for many different purposes but to measure the communication rate, the baud rate is

the best rate which had been defined.In most of the cases the baud rate had been used in thesense of symbol rate which exactly show that how much of the speed had been in thetransmission of the data or some other work which had been carried out through the systems.It is also at times used for some codes as well where the user is using it in determining thetime that had been taken by the code and in its testing and the running phase. It must be takeninto account that the baud rate must not be misused with the gross bit rate. In other terms the

baud rate is used to describe the changes that are brought in the pr second line that are beingentered. It had been found out that the bit of the information can be easily converted intoelectrical changes as well. The baud rate of data transmission in both transmitter and receiver (which in this case are system and RF transmitter) must be same for maximum efficiency.

The baud rate of a transmitter must always be less than transmitter for the data transmission totake place. If the baud rate of transmitter is le ss than receiver then data transmission doesn t


21/24

21

take place (e.g: baud rate of transmitter is 10kbps n that of receiver is 2kbps then there is noway receiver can pass the remainder of 8 kbps of data)

Fault in the transmitter due to corrupted encoder which cant sendproper signals even if there are proper commands given to the IR transmitter by the computer via the serial port:

An encoder is a device, circuit, transducer, software program, algorithm or personthat converts information from one format or code to another, for the purposes of standardization, speed, secrecy, security, or saving space by shrinking size. In this case theencoder in the IR transmitter converts the data received into the required mode of transmission to be received by the receivers in the robots.

Fault in the architecture of the robot:

The primary fault may include battery wherein the power supplied from the battery is notconstant. Secondary fault may perhaps be decrease in the power capacity of the batteriesowing to large stagnant time between acquisition and application times. For much of theexperiment the running time for the battery during the testing was below 20min, which is theapproximate running time of the battery for a complete charge calculated in accordance withthe specifications. This may be due to:-

1)faulty charger

2)faulty battery.
http://en.wikipedia.org/wiki/Encodinghttp://en.wikipedia.org/wiki/Codehttp://en.wikipedia.org/wiki/Codehttp://en.wikipedia.org/wiki/Encoding


22/24

22

IX. Remedies:-

1. Software Incompatibility Issue:-

The mirosot software that we used in our experiment was only compatible with windows 2000/98 andwas incompatible with the operating systems usually used now days, so the software must be updatedto its higher versions and proper addressing should be done to avoid this incompatibility issue.

2. Serial Port Issue:-

The problem with the serial port due to its hardware incompatibility with the RF Transmitter may lead

to some serious issues that we need to work upon. The serial port enables the hardware to run byserializing the data, i.e. it takes a byte of data and transmits the 8 bits in the byte one at a time, theserial port takes 8 times longer to transmit the data, so while processing the serial port or the COM

port might crash which may lead to further inconvenience. Therefore, in order to overcome this problem we consider the following procedure:

OPEN "COM1:300,N,8,1,BIN,CD0,CS0,DS0,OP0,RS,TB2048,RB2048" AS #1

(This OPEN is FOR RANDOM access.) The following is an explanation of each recommended parameter used in this OPEN statement:

The higher the baud rate, the greater the chances for problems; thus, 300 baud is unlikely to give you problems. 2400 baud is the highest speed possible over most telephone lines, due to their limited high-frequency capability. 19,200 baud, which requires a direct wire connection, is most likely to cause

problems. (Possible baud rates for QuickBasic are 75, 110, 150, 300, 600, 1200, 1800, 2400, 4800,9600, and 19,200.).

Parity usually does not help you significantly; because of this, you should try No parity (N).

For those devices that require parity, you should use the PE option (Parity Enable) in the OPEN COMstatement, which is required to turn on parity checking. When the PE option turns on parity checking,a "Device I/O error" occurs if the two communicating programs have two different parities. (Paritycan be Even, Odd, None, Space, or Mark). For example, a "Device I/O error" occurs when two

programs try to talk to each other across a serial line using the following two different OPEN COMstatements:

OPEN "COM1:1200, O, 7, 2, PE" FOR RANDOM AS #1

And

OPEN "COM2:1200, E, 7, 2, PE" FOR RANDOM AS #2

If the PE option is removed from the OPEN COM statements above, no error message

displays.


23/24

23

The above example uses 8 data bits and 1 stop bit. Eight data bits requires No parity (N), because of the size limit for Basic's communications data frame (10 bits).

The BIN (binary mode) is the default. Note: The ASC option does NOT support XON/XOFF protocol, and the XON and XOFF characters are passed without special handling.

Ignoring hardware handshaking often corrects many problems. Thus, if your application does notrequire handshaking, you should try turning off the following hardware line-checking:

CD0 = Turns off time-out for Data Carrier Detect (DCD) lineCS0 = Turns off time-out for Clear to Send (CTS) lineDS0 = Turns off time-out for Data Set Ready (DSR) lineOP0 = Turns off time-out for a successful OPEN

RS suppresses detection of Request to Send (RTS).

For buffer-related problems, try increasing the transmit and receive buffer sizes above the 512-bytedefault:

TB2048 = Increases the transmit buffer size to 2048 bytes.RB2048 = Increases the receive buffer size to 2048 bytes.

3. How to solve the architecture issues of the robot:

Architecture issues of the robot may include faulty battery, faulty connections and faulty charger. All

these problems can be fixed by replacing the battery and checking the connections properly. The backup of the battery should be sufficient enough to carry out the experiment, so in order to solve thisissue, battery problem is the foremost issue that should be taken care of. After solving the battery

problem, all the wired connections in the Microrobot should be checked properly. One more problemthat we normally encounter while carrying out the experiment is that we don t find proper voltagevariation at each terminal and the pins of the charisma board, so after each trial the voltage readingsshould be taken with the help of a multimeter. Replacing the charger might also solve this issue.


24/24

24

X. References :[1] Jihad Reaidy, Daniel Deip, Pierre Massote, Managem ent and control of Complex Production

Systems: Co- opetition through Game Theory Principles and Agent based Information Systems. [2] Vincent A. Cicirello, A Game Theoretic Analysis of Multiagent Systems for Floor Shop

Routing, Tech. Report, CMU-RITR-01-28, Robotic Institute, Carnegie Mellon University, 2001.[3] Felix Brandt, Felix Fischer, Marcus Holzer, On Iterated Dominance, Matrix Elimination and

Matched Paths, Symposium on Theoretical Aspects of Computer Science 2010, (Nancy, France), pp.107-118.

[4] Mohamed J maiel, Ahmed Hadj, AmiraRgaieg, An operational semantics dedicated to thecooperation of cooperating agents,Intelligent agent and Multi -Agent systems, 5 th Pacific RimInternational Workshop on Multi-Agent Systems, PRIMA 2002, Japan, August 2002Proceedings.

[5] Vishnu R. Desaraju, Jonathan P. How, Decentralized Path Planning for Multi -Agent Teams inComplex Environment using Rapidly- exploring Random Trees, IEEE Int. Conf. on Robotics &Automation, 2011, Shanghai China, pp.4956-4961.

[6] H.V.D. Parunak, S. Bru eckner, Mitch Fleischer, James Odell, A design Taxonomy of Multi -Agent Interaction, Agent -Oriented Software Engineering IV, Melbourne, AU 2003, pp 123-127.

[7] K.H. Park, Y.J. Kim, J.H. Kim, Modular Q -learning based Multi-Agent Cooperation for robotsoccer , Robotics and Automation Systems(2001) , Vol.35, pp. 109-122.

[8] H.S. Shim, H.S. Kim, M.J. Jung, I.H. Choi, J.H. Kim, J.O. Kim, Designing distributed controlarchitecture for cooperative multi-agent system and its real-time applica tion to soccer robot,Robotics and Automation System(1997), Vol.21, pp. 149-165.

[9] N.B. Hui, D.K. Pratihar, Comparative study on some navigation schemes of a real robot tacklingmoving obstacles, Robotics and Computer Integrated Manufacturing(2009), Vol.2 5, pp. 810-828.

[10] H. Qianwei, M. Hongxu, Z. Hui, Collision avoidance Mechanism for Multi -Agent Systems,Proceedings of 2003 IEEE Int. Conf. on Robotics, Intelligent Systems and Signal Processing,China (2003).

[11] E.S. Kazerooni, K. Khorasani, Multi -Agent Te am Cooperation: A Game Theory Approach,Automatica(2009), Vol.45, pp. 2205-2213.

[12] R.B. Myerson, Game Theory: Analysis of Conflict, Harvard University Press,[13] Mirosot Soccer Robot The robots are developed for FIRA Mirosot in which two teams of

five or eleven robots competes in a soccer game. The URL: http://www.robo-erectus.org/Mirosot/Mirosot.php.

[14] Soccer Robots and Accessories RS -MIROSOT-100 Advanced Soccer Robot. TheURL: http://www.robotstorehk.com/soccer/soccer.html.

[15] How Serial Ports work from the website www.howstuffs work.com . The url:http://computer.howstuffworks.com/serial-port1.htm [16] Serial port problem solutions from the website:

http://support.microsoft.com/kb/39342
http://www.robo-erectus.org/Mirosot/Mirosot.phphttp://www.robo-erectus.org/Mirosot/Mirosot.phphttp://www.robotstorehk.com/soccer/soccer.htmlhttp://www.howstuffswork.com/http://www.howstuffswork.com/http://www.howstuffswork.com/http://www.howstuffswork.com/http://www.howstuffswork.com/http://computer.howstuffworks.com/serial-port1.htmhttp://computer.howstuffworks.com/serial-port1.htmhttp://computer.howstuffworks.com/serial-port1.htmhttp://www.howstuffswork.com/http://www.robotstorehk.com/soccer/soccer.htmlhttp://www.robo-erectus.org/Mirosot/Mirosot.phphttp://www.robo-erectus.org/Mirosot/Mirosot.php

Documents

Game Theory based Path planning for Multi-agent system