Systems of Systems Communication forHeterogeneous Independent Operable Systems

Kranthimanoj Nagothu, Student Member IEEE, Ted Shaneyfelt, Student Member IEEE,Pactrick Benavidez, Matthew A. Jordens, Member IEEE, Srinath kota

and Mo Jamshidi, Fellow IEEEAutonomous Control Engineering (ACE) Center and ECE Department

The University ofTexasSan Antonio, TX, USA

Email :{ kranthimanoj.nagothu, matthew.joordens, ted.shaneyfelt }@utsa.edu,p_b_2003@hotmail.com, akray@iitk.ac.in, moj@wacong.org

Fig. 1 Systems of Systems main Characteristics [6]

survey on system of systems, there are several definitions.Detailed literature survey and discussions on these definitionsare given in [5]. All of the definitions of SoS have their ownmerits, depending on their application. Our favorite definitionis "Systems of systems are large-scale concurrent anddistributed systems that are comprised of complex systems."Fig. I. Depicts characteristics of SoS.

The interoperability in complex systems (i.e. multi-agentsystems) is very important as the agents operate autonomouslyand interoperate with other agents (or non-agent entities) totake coordinated actions. Interoperability requires successfulcommunication among the systems. where, the systems shouldcarry out their tasks autonomously in part, whilecommunicating with other systems in the SoS in order to

ComplexDynamicIssues

ImportantContextualInfluences

Self-OrganizingCapabilities

Counter­ProductiveSolutions

Interoperabilityand

Recomposability

IndependentComponent

Systems

Adapted from Reckmeyer

Technical &Non- Technical

FactorsAdvancedCyberneticCapabilities

AmbiguousChanging

Boundaries

EmergentNon-LinearProperties

EvolvingComplex

Relationships

Counter­IntuitiveBehavior

Index Terms- Systems of Systems, UnderwaterCommunication, Surface communication, Swarm Robotics

Abstract- Swarms of robots in heterogeneousenvironments working together in a System ofSystems, raisethe need for suitable inter-swarm communication. This paperpresents a potentially viable solution. Communication for landswarms was found to be successful through ZigBee RadioModems, and a suitable counterpart is necessary forunderwater swarms in a system of systems. An extensiblestandards based protocol to accommodate different types ofdata was developed for use among the swarm robots. Thiscommunication system allows for dynamic swarm expansion,where new members can be added to the swarm family. Thisenables coordination among robots within and betweenswarms in a system ofsystems framework

The concept of SoS is essential to effectively implement andanalyze large, complex, independent, and heterogeneoussystems working (or made to work) cooperatively. The mainthrust behind the desire to view the systems as an SoS is toobtain higher capabilities and performance than would bepossible with a traditional system view. The SoS conceptpresents a high-level viewpoint and explains the interactionsbetween each of the independent systems. However, the SoSconcept is still at its developing stages. Based on the literature

I. INTRODUCTION

The Autonomous Control Engineering (ACE) lab of TheUniversity of Texas at San Antonio is working towards a

System of Systems of Robotic Swarms with cooperationamong swarms in air, land, and sea. [I], [2]. Robotic swarmscould be used as part of a System of Systems for applicationssuch as augmentation of an environmental researchknowledge base [3], sensor network type application [4],military, security, aerospace and disaster management.

optirmze actions for the overall benefits of the SoS, ratherthan just for themselves. The Integration implies that eachsystem can communicate and interact (control) with the SoSregardless of their hardware and software characteristics. Thismeans that they need to have the ability to communicate withthe SoS or a part of the SoS without compatibility issues suchas operating systems, communication hardware, and so on.For this purpose, an SoS needs a common language itscomponents can speak. Without having a common language,the SoS components cannot be fully functional and the SoScannot be adaptive in the sense that new components cannotbe integrated to the SoS without major effort. Integrationshould also consider meaningful control aspects of the SoS.For example, a system within an SoS should be able tounderstand commands and/or control signals from other SoScomponents [6].

In order to achieve some of main characteristics of system ofsystems approach, communications play a vital role. Thispaper investigates a means of extending the protocol forcommunicating among heterogeneous interoperable systemsas depicts in Fig. 2. In our case, robotic swarm systems inheterogeneous environments (land, water and air) are to betaken in to consideration as a larger SoS. The next sectionbriefly reviews over-the-air and underwater communicationamong autonomous vehicles. Section III is aboutcommunication between surface and underwater vehicles.Section IV is about communication between unmanned airvehicles and ground.

Fig. 2 Communication among HeterogeneousInteroperable Systems

II. OVER-THE-AIR AND U NDERWATER COMMUNICATION

Swarms of unmanned vehicles have the potential torevolutionize our access to the environment and to address thecritical problems faced by the community such assearch/rescue, mapping, climate change assessment,inspection, habitat monitoring, mine counter measures andscientific studies in diverse areas. Localization, navigation,and communication are three primary requirements for roboticswarms. In getting swarms to solve problems comprehensively ,a key issue is communication. Communication can beimplemented in numerous ways including radio frequencymodulation, acoustic propagation, and fiber-opticcommunication. Acoustic signals propagate well underwater,but they face problems due to very limited bandwidth, largesignal propagation time. Radio modems work well over theair, and could be used for underwater communication if thepropagation and bandwidth characteristics underwater wereimproved over conventional radio frequency modulation. Thelimited bandwidth of the low frequency signals typically usedunderwater severely limit communication underwater. Thenear and far problem occurs when an acoustic unit may nottransmit and receive at the same time because oflocal transmitpower levels. For acoustic underwater communication, largepropagation delays involved in acoustic propagation are in therange of seconds. All these factors lead to developing alternativetechnology to communicate effectively underwater. Researchershave attempted to address these issues. A few have tried to usefiber-optic cables to implement underwater communication,which proved to be expensive, requiring high maintenance andwere prone to fiber-optic cable damage. Looking in to all thesefactors we considered radio modems for communication [7].

The radio modems chosen for over-the-air communication areZigbee modules. Zigbee is a low-power wirelesscommunication technology and an international standardprotocol for the next-generation wireless networking. Itreduces the data size and allows for lower-cost networkconstruction with simplified protocol and limitedfunctionality. Zigbee uses the MAC layers and PHY layersdefined by IEEE® 802.15.4, which is the shortest- distancewireless communication standard for 2.40Hz [8]. The benefitsof Zigbee are that it supports three different topologies: star, mesh,cluster-tree networks , robustness, simplicity, low-powerconsumption and mesh networking. 802.15.4 provides arobust foundation for Zigbee, ensuring a reliable solution innoisy environments. Finally , multiple levels of security ensurethat the network and data remain intact and secure [9].

BASE

Fig. 3 Experimental Setup

WHIP, CHIPorRPSMAAntennas

REMOTE

Algorithm/or proposed Approach

1) Determine the position of all the existing nodes using thebroadcasting method. In broadcasting method the master nodesend packets to all other the nodes. It receives back theacknowledgment from other nodes with their respectivepositions.

2) The shortest paths are calculated between the master nodeand destination node. The shortest paths refer to that with thefewer hops from the master node to the destination node.

3) Ifthere are two or more shortest paths, the most reliablepath is chosen from the shortest paths.

The problem, however, with underwater communicationsusing radio is radio doesn't work very well, if at all,underwater. To achieve a distributed protocol network forunderwater communication, we need to find out the range ofeach module in underwater. Although communication incontaminated or salty water seriously degrades RF signalpropagation, we have continued looking for an improved RFsolution through wideband communication.

Initial research into OFDM provides promise in this area, sothat we expect the range of radio modem underwater to besufficient for cellular type networking. The next issue to bediscussed is how to communicate between these radiomodems underwater to achieve effective communicationamong the small fleet of Autonomous Underwater Vehicles(AUV) Unmanned Air Vehicles (UAV), and other swarms tosolve a problem cooperatively.

Proposed Approach to Swarm Networking

In the proposed approach we assume the position of eachswarm robot is known by existing localization techniques[10]. The position of robot is given in the form of (X-axis, y­axis, and Z-axis). Consider the underwater scenario in Fig. 5.In this case we consider these small circles representing nodesthat are present in AUVs. We need to communicate amongAUVs. A node should send some information to 0 node toestablish communication. In this approach position of therobot is also included with the acknowledgment. Every nodehas also a unique identification number, and every packet hasunique identification number corresponding to its destination(In this case the packet identification number is destination 0identification number). Each time a node receives a packet, itfirst verifies that its identification number matches the packetidentification number. If so it stores the packet in the memoryand in tum broadcasts an acknowledgement, else transmits thepacket to neighboring nodes. In the proposed approach mastercan be switched in case of failure in the system (in this case Ais the master node). Although this example is for underwatervehicles, the same techniques could be adapted for use also inthe air for UAVs or on land for swarms of land rovers.

4) Reliable path is calculated based on the physicaldistances between the nodes.

5) Select the largest physical hop distance from each shortestpath. The largest physical hop is calculated using thefollowing distance formula.Distance

Formula=~(Xa - Xb) /\ 2 + (Ya-Yb) /\ 2 + (z, - Zb) /\ 2

6) When comparing the largest hops from each shortest path,the smallest of largest hop is chosen.

7) Reliable path is decided based on the result of step 6.

8) Each time a node acknowledge to master node it alsoupdates its position. Based on this, the master node verifies ifthere is any change in the position of the nodes.

9) If there is any change in the position of nodes, go to step 1.

10) If there is no change in the position of the nodes use theexisting path to send all the packets.

Finally, the packet reaches destination node O. This approachrequires at least 4 hops to receive a packet from source (A) todestination (0). As the number of hops decrease, the timedelay and power consumption also decrease. The proposedapproach achieves effectiveness in communication betweenautonomous vehicles.

This technique suffices for communication within a commonmedium such as underwater swarms, or swarms of unmannedair vehicles such as quad-rotors. However, to communicatebetween an underwater vehicle and a quad-rotor above thesurface, additional techniques must be employed. One suchtechnique will be discussed in the following section.

1Underwater

----\8/-)----------(1)

The first method is to use a directional antenna to direct thesignal from the gateway vessel on the surface to a swarmunderwater.

Where OJ is the frequency , f.l is the permeability of the

water, I; is the permittivity, ()" is the electricalconductivity.The ACE lab has been using XBee Pro modules forcommunications among land based vehicles, and isexperimenting with using OFDM for communicationsbetween underwater vehicles. The overall solution willemploy a surface vessel with both communication underwaterand on land to act as a gateway between swarms in bothenvironments. Where the propagation is insufficient to reachdirectly, several methods could be used either individually orcombined.

---0----------------0~C ~-----

------->..,0~------------

----u

Fig. 5 Scenario of arrangement of AUV's

A second method is to use an optic fiber or wire-linemechanism for extending the antenna underwater toward theswarm.

III. UNDERWATER TO SURFACE COMMUNICATION

A third method is to use intermediate relay swarm robotsbetween the surface vehicle's antenna and the underwaterswarm.

In this section our aim is to establish communicationconnectivity between underwater and surface vechiles. Wire­line communications could be established with all submarines,but the restrictions on mobility such as entanglement suggestwireless communications should be accommodated at somepoint, whether at the end of a wire, or from a communicationdevice at the surface. Once communication is made to thesurface, a surface vessel could relay signals to other swarmsoutside of the water. Wireless communications includes sonar,laser, and radio frequency. Laser suffers from being difficultto point, as the Underwater Autonomous Vehicles (UAVs)need to locate one another , and even then murky water couldbe a common problem. Sonar travels well underwater, but thesignal travels slowly with low bandwidth. High endcommercial underwater sonar modems are limited to 9600baud. An alternative may be OFDM radio communications.The main disadvantage of radio communications is that itsuffers from heavy attenuation underwater due to the skindepth associated with impure water's conductivity. Skin depthmeasures the distance a radio signal can travel through amedium before attenuating to e-1 of the original signal power,and is calculated by:

A fourth method is to take a hybrid approach , where, forexample, intermediate relay robots may themselves reel outantennas toward one another to reach the swarm from thesurface vessel.

IV. AIR TO GROUND COMMUNICATION

In order to interact between these two physical domains, it isneeded to create a viable communication system with acommon protocol that can be used on various platforms. Thecommunication protocol must allow a dynamically expandableswarm, where additional robots can be added easily during areal-time application. Additionally, the protocol must also beflexible enough to accommodate different types of data suchas image, video, GPS locations, control messages etc. Exactrequirements of data types in the communication protocol canvary depending upon the swarm mission. Such requirementsof a communication protocol for a swarm level mission can bedetermined from the following scenarios. Fig. 9 depict aswarm of various robotic platforms collaborating in air andground domains for a multi-domain system.

Electronic communication can be implemented in wire-lineand wireless configurations. Practical limitations of mobility

restrict the extent to which wire-line communication can beused. Wireless communication can be achieved in many waysincluding acoustic propagation and radio-frequency (RF)communication etc. Systems utilizing acoustic propagation asa means of communication face many drawbacks. All theselimiting factors lead us to choose RF technology to provide asolution for our swarm communication system.

Fig. 9 Scenario of interaction between two physicaldomains

Protocol Design:

ZigBee based radio modems provide the PHY and MAClayers for a communication protocol. It allows the freedom ofusing a custom protocol for the swarm of robotics. Serial LineInternet Protocol (SLIP) provides us the benefits of lowoverhead requirements and a simple base to create acustomized protocol to fit the needs of the swarm [12]. SLIPrequires the use of a special character set for a control method:"flag", "end", "escape", "modified flag", "modified end", and"modified escape" . Messages transmitted using SLIP willbegin with a l-byte flag character and end with a l-byte "end"character. When the transmitted data matches the charactersused in the special character set, the data is replaced with anescape character followed by a "modified" version of theoriginal byte. Any array of commands could also be sent inthe SLIP protocol which does not require any knowledge ofdata size. This allows the transmission of extensiblemessages. This will greatly reduce the need forstandardization in order of specific bytes in both thetransmitted and received packets.Many other protocols specify source and address fields in theheader of a transmitted message. Addressing and routing canbe handled in this source/destination format by including bothdomain and swarm type identifier in the transmitted messagedata. Swarm masters can check a received message for thedomain and then the swarm identifier to determine if themessage is for their swarm or not. Slave members of a swarmcould check for the swarm identifier and a specific robotidentifier to understand whether the message is for them ornot. If the message lacks a specific robot identifier, then themessage is being sent to the master of its ground swarm. Ifmessages are to be broadcasted to all members of all swarms,then a broadcast type identifier will override the necessity of asource and address field.

One major limitation not addressed by the SLIP protocol iserror correction. The simplest form of error correction is asimple checksum. Simple checksums have the ability to beable to detect either one or two bit errors. A more robustapproach involves a cyclic redundancy check (CRC). A CRCis more robust than a simple checksum because it has theability to check multiple bit errors. A major drawback tousing a CRC is that the computational time is greater than thatfor a simple checksum; however the benefit of checkingmultiple bit errors when they occur is much greater than thecost of computation time for our robotic swarm. There aremany different CRC checksum standards that exist fordifferent levels of error checking, correction and data sizes.The specific CRC that we have considered in this work is aCRC-CClT which has a divisor polynomial OfX16 + X12 + x5 +1.This can be implemented by processing one byte at a timeand adding 2 bytes of overhead to a transmitted message.Low overhead, robust error checking and an option for anextensible message data allow for a simple, expandableprotocol that can be used on various platforms. Wherebandwidth and processing resources permit, extensiblemarkup language may be employed in the messages.Otherwise, the messages can be binary SLIP packetstranslated to XML as they are transmitted through higherbandwidth network nodes.

V. AIR TO S URFACE COMMUNICATION

Similar to air to ground communication, air to surfacecommunications can be achieved . These surface vechiles canrelay messages to underwater vechiles and form a Systems ofSystems Communication for heterogeneous independentoperable systems.

III. CONCLUSION

The ACE center is focusing on developing systems of roboticsystems technology for heterogeneous environments. Wehave demonstrated significant progress in communicationtechnology towards that goal. To accomplish this, wephysically tested low-cost wireless communications in diverseenvironments and mediums including underwater. Havingestablished that low-cost wireless communication can beaccomplished in these environments, we have devisedprotocols for communication among robots within swarms andbetween heterogeneous swarms. This communicationtechnology has been designed to be extensible with intent ofapplication in net-centric systems of systems to benefitmankind through cybernetics.

REFERENCES

[I] Ted ShaneyfelI, Mo Jamshid i, "Net-Centric System of SystemsInvolving Robotic Swarms across Air, Land, and Sea," inUniversity ofTexas at San Anton io 2007 Engineering, Science, andBusiness Confere nce, San Antonio, Texas, USA, 2007.

[2] Robert J. Cloutier, Michael J. DiMario, Hans W. Polzer, "Net­Centricity and System of Systems", System of Systems ­Innovation for the 21st Century, Chapter 9 Wiley & Sons 2008.

[3] S. S. Erdogan, Ted Shaneyfelt, Andrew Honma and Cam Muir,"Integrated Knowledge Base for Environmental Research", Proc.IEEE International Conference on Autonomic and AutonomousSystems International Conference on Networking and Services(ICAS'05 and ICNS'05), October 23-28, 2005, Papeete, Tahiti,French Polynesia.

[4] Prasanna Sridhar, Asad M. Madni, and Mo Jamshidi, "HierarchicalAggregation and Intelligent Monitoring and Control in Fault­Tolerant Wireless Sensor Networks", IEEE Systems Journal, 2007

[5] DiMario, M., 1., "System of Systems Interoperability Types andCharacteristics in Joint Command and Control," Proc. of IEEEInternational Conference on System of Systems Engineering, LosAngeles, April 2006.

[6] Ferat Sahin, Prasanna Sridhar, Ben Horan, Vikraman Raghavanand Mo Jamshidi, "Systems of Systems Approach for ThreatDetection and Integration of Hetrogeneous Independently OperableSystems", in Proc. IEEE Int. Conf. Syst, Man, Cybern, 2007.

[7] Kranthimanoj Nagothu, Matthew Joordens, and Mo Jamshidi,"Communications for underwater Robotics Research platforms," inproc IEEE Systems Conference, Montreal, Canada, 2008,p. 6.

[8] Sinem Coleri Ergen, "Zigbee /IEEE 802.15.4Summary", Sep. 2004.

[9] ZigBee Alliance, ZigBee Specifications Version 1.0,San Ramon, CA, USA, December 2004. [Online].

Available: www.zigbee.org

[10] Navinda Kottege and Uwe R. Zigmmer, "Relative Localizations forAUV swarms", in Proc.Int.Symposium on Underwater Technology,"Tokyo, Japan, 2007.

[11]

[12] Patrick Benavidez, Kranthimanoj Nagothu, Anjan Kumar Ray ,Ted shaneyfelt, Srinath Kota and Mo Jamshidi "Multi- DomainRobotic Swram Communication System ," in paper submitted toIEEE SoSE Confernec, Monterey, CA, USA, 2008, p. 6.