TOWARDS A COMMON UNDERSTANDING

OF THE DIGITAL PHEROMONE

Hans Dermot Doran

Institute of Embedded Systems, Zurich University of Applied Sciences, Winterthur, Switzerland

Keywords: Pheromones, Artificial intelligence, Robotics, Industrial communication, Communication theory,

Autonomous systems, Mobile robots.

Abstract: In this paper we critically evaluate the research on digital pheromones to date and conclude that the wide

variance in the understanding of what a digitised pheromone is serves to defocus research. We examine the

classical pheromone-use algorithm, the ant algorithm and conclude that as such it has not been proven

feasible for practical use. By examining the failure of proposed applications we derive an application where

pheromones appear to offer added value. On critically evaluating an initial implementation we note its

success but point out that lacking the understanding of biological pheromones serves to hinder research in

digital pheromones in general and bio-inspired robotics in particular. We propose a set of rules and urge

researchers to critically evaluate them.

1 INTRODUCTION

The general conceptual framework around this

position paper is the argument that bio-inspired

algorithms in general and pheromones in particular,

which have been suspected of bringing efficiencies

to real-world problems, are not as simply transferred

to real-world problems as the state of research

implies but require substantial applied research

which leads to a re-evaluation of previously held

opinions. In particular the paper presents the

argument that the state of the art in pheromone

research has not brought forth any applications that

can reasonably use pheromones and that the actual

implementation of these pheromones are so far

removed from the biological understanding of the

term as to mutate to mere marketing slogans. We

present an application which we believe to be as real

an application as to deserve the term pheromone but

show that even then it can be argued that the notion

of digital pheromone ought to be qualified by

quotation marks.

The paper is structured accordingly – we begin

by examining the biological definition of a

pheromone before critically reviewing the current

state of research on the digital variant of the topic.

We evaluate known use cases and construct what we

consider to be a viable use case and defend this

principle. We then presents preliminary result of an

implementation and draw the conclusions which are

then discussed in the broader context of this

argument.

Final conclusions follow with an outlook on

further work.

2 PHEROMONES

2.1 Natural Pheromones

Pheromones are well described (Wyatt, 2003) but in

summary are known to science as complex organic

compounds, and mixtures thereof, excreted by

animals and insects for message passing purposes.

Pheromones are generally, but not canonically,

classified by the reaction they invoke in receptors.

Propagation is by diffusion, accelerated by velocity

and concentration of excretion as well as the

intrinsic cohesion and medium composition

properties of the carrier (air, water). Reception is for

homogeneous message passing, apparently, an exact

science in that the receptors can be very

discriminating with respect to direction, in some

cases in three dimensions, and distance, some moths

and butterflies can famously detect potential mates

from some 10 km away. For heterogeneous

communication all or a subset of the information

intentionally transported may be, either intentionally

176

Doran H..

TOWARDS A COMMON UNDERSTANDING OF THE DIGITAL PHEROMONE.

DOI: 10.5220/0003572901760181

In Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics (ICINCO-2011), pages 176-181

ISBN: 978-989-8425-74-4

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

or unintentionally detected by other species.

What is known is that certain animals will re-

orientate their physical position according to

whether they wish to maximise or minimise the

reception of pheromones, what isn’t so well

discussed is whether – especially with airborne

pheromones – the act of excretion takes advantage

of ambient media conditions. There are simple

examples to suggest this is sometimes the case, dogs

and lamp posts spring to mind. More complex

examples quote bees which excrete pheromones and

accelerate movement of their wings in order to

facilitate distribution (Reinhart, 2009).

2.2 Fundamentals of Technical

Pheromones

From a technical point of view pheromone

transmission represents connectionless wireless

transmission, stochastic propagation with signal and

media dependent dispersion and attenuation.

Reception results in concentration dependent pulse

streams. Signal filtration is at point of reception.

Given that technical communication systems

depend on some form of determinism with respect to

probable area of distribution of transmitted signal,

when using pheromones we may assert:

Rule 1: Technical implementations of

pheromones must show some awareness of ambient

media conditions. If it is not otherwise possible

digital pheromones shall implement some time

based degradation profile.

Rule 2: It is acceptable for mobile units wishing

to excrete or receive pheromones to deviate from

their current path of motion to do so.

Rule 3: Pheromones serve for excreters and

receptors to interact within temporal and geographic

limits defined by the medium of choice.

As a complex chemical, sometimes a mixture

thereof it is the presence of a pheromone that

denotes the primary information value. The

secondary information is given by the concentration,

or the rate of change of concentration.

3 TECHNICAL

IMPLEMENTATIONS

OF PHEROMONES

3.1 “Virtual” Pheromones

Payton et. al’s. work is well cited with respect to

their pherobot project during which he coined the

phrase “Virtual Pheromone”. (Payton, 2001, 2003,

2004) They envisioned the search and rescue use

case and whilst they begin promisingly, detailing

some of the simpler characteristics of pheromones, it

becomes hard to reconcile priority transmission,

message passing and data request primitives with the

concept of a bio-inspired pheromone. Although the

term “Virtual Pheromone” found use with other

researchers, in essence his solution reduces to a

mixture of a directed transmission/re-transmission

service combined with elements of embodied and

situated communication.

The message complexity suggested by Payton

et.al. was vastly reduced by Campo et.al (Campo,

2010). to three message types who, following other

authors (Ducatelli, 2008), conceptualised message

passing as an ant which laid pheromones along a

chain of robots whilst being passed along this chain

by the robots themselves. The concept has much

merit, but is an abstraction removed from the

physicality of laying down a trail and acting on it

like the bio-inspired counterparts.

3.2 Pheromone Storage

Storage of these imagined pheromones is always an

issue. Most research that requires a bio-inspired

model and a pheromone tends towards research in

swarm robotics which in turn generally means that

short and medium term coordination is the task to be

solved by the use of these pheromones. Meng

(2008). built a map of swarm participants and their

respective pheromone densities. Borzello and

Merkle (2005) deposit a “pheromone”, whose

structure is unclear, on an uncompleted task by a

robot who then attempts to find another task leaving

the next random-walking robot to chance across the

task and attempt to complete it. The work, located

solely in the virtual world, attempts to use the ant

algorithm in an attempt to prevent task-deadlock in

multi-robot cooperative scenarios. As such the

pheromone loosely corresponds to a signal

pheromone, a pheromone designed to trigger a short-

term behaviour alteration. In this case the

pheromone triggers a state change in a state

machine, the behavioural pattern itself is not

changed and the pheromone does not serve to attract

the mobile robot nor does it induce any kind of

cooperative behaviour making it difficult to consider

it a “proper” pheromone. Both Susnea et.al (2009)

and Gunzinger and Pffifner (2008) use a central

server to map the pheromones onto virtual space and

provide these details to real-world requesting robots.

The use of air as a medium has also been

researched. Kuwana et.al, (1995) in earlier work

attached live moth antenna to a mobile robot to

TOWARDS A COMMON UNDERSTANDING OF THE DIGITAL PHEROMONE

177

follow moth pheromones. A practical application of

this technique would however depend on both

keeping the moth antenna alive over a longer period

of time and being able to generate the moth

pheromone in some manner. Russell and his

researchers (Purnamadjaja, 2004) tackled this

problem by using inorganic chemicals and gas

sensors for pheromone generation/detection.

Fujisawa et al. (2008) use ethanol as a pheromone.

There are other deposition media considered

such as ink on substrate (Svennebring, 2004) or UV

on phosphorescent coating (Mayet, 2010) but whilst

general feasibility may have been shown these do

not represent solutions that are likely to be taken up

by industry. Several researchers including Mamei

et.al. (2005) Heiranto (2009) and Doran et.al.

(2009b) have experimented with the idea of using

RFID tags. Heiranto concentrates on imagining a

floor of RFID tags whilst Doran and Mamei imagine

discretely positioned tags within a building.

3.3 Pheromones and Methodology

Interestingly enough Gunzinger found that the ant

algorithm was, for his particular scenario noticeably

less efficient than the Dijkstra algorithm in finding a

path with the help of pheromones but unfortunately

failed to quantify this. The use of a bio-inspired

model in conjunction with a mathematical algorithm

is not new and but does lead us to several questions.

The first is as to the general methodology

concerning the use of bio-inspired models. The

author has experienced in other projects, notably the

implementation of fish swarming algorithm that the

algorithm appears to need continual refinement

which is generally mathematical in nature, before

being implementable in hardware. This may be due

to the fact that a bio-inspired algorithm must

generally be expressed mathematically before initial

implementation therefore further refinement is by

default mathematical and the Gunzinger case is

merely the extreme case where the refinement of a

bio-inspired algorithm is simply not efficient given

known mathematical alternatives. It may also be due

to the fact that researchers are trained to research in

this way and that a lack of methodological flexibility

precludes the discovery of alternatives. In either case

it would thus appear probable that the act of

observation and expression of a bio-behaviour in

mathematical terms causes the algorithm to lose the

robustness that the observer wished to capture in the

first place.

Also, by observation, the author has noticed that

the necessary input to enact a behavioural pattern

generally cannot be solely received from one

sensory input - is a second or third sensory input is

required. For example fish schooling can be

simulated by using an interpretation of the lateral

line but the creation or breakup of a school requires

either a short-cut using either, for instance, a random

walk or optical species recognition. Given that

neither a real nor artificial fish will grow and utilise

eyes solely for swarming purposes but as

Lichtensteiger (2005) shows, albeit for flies,

artificial evolution of eye morphology leads to

single-use optimisation. It is unfortunate he omitted

to test quality of second and third priority tasks.

These observations inevitably lead to the question as

to whether, and if so with what methodology,

behavioural patterns can be isolated and

implemented whilst avoiding a holistic approach to

robot development.

3.4 Implementation Architectures

Controller architectures also play an important role.

In many experimental systems standard controllers

using some form of state machine are used. Whilst

state machines are often used in embedded systems

mapping a behavioural pattern into a state machine

is the engineering equivalent of expressing an

observed algorithm in a mathematical form, the

essence is bound to get “lost in translation”. The use

of state machines to switch between behavioural

patterns has, according to the authors research, not

yet been researched, but given the experience at the

sensor level where some convolution of sensor

inputs produces an output, it is unlikely to work very

well. Other controller architectures use neural

networks and evolve behaviour. Neural networks

have so far, by and large, failed to impress industry

due to the fact that training is lengthy and is both

non-deterministic and non-reproducible in output.

Whilst self-modelling, as shown by Bongard et.al.

(2006), is promising, it will be some time before we

see such architectures implemented.

Ants are relatively easy things to conceptualise

but, the drive towards cheap microbots

notwithstanding, robots cost money, ants don’t and a

lost ant won’t be missed whereas a lost robot will.

Therefore the task that the robot must fulfil should

be equivalent to the complexity (and by proxy cost)

of the robot. If we orientate ourselves to animals

which can be used in various scenarios then we need

something at least of the relative complexity of a

dog (Doran, 2009a). On the other hand there doesn’t

seem to be any reason why one can’t borrow the

sensor system of an ant and graft it onto a robot dog.

Given a pheromone is intimately connected with

a behavioural pattern (searching for and identifying

ICINCO 2011 - 8th International Conference on Informatics in Control, Automation and Robotics

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pheromones) and the switch between behavioural

patterns this must be reflected in the controller

architecture. Therefore the robot designer must be

able to combine the behavioural patterns of various

models to make one robot.

In conclusion and summary:

Rule 4: A pheromone may be used to switch

from one behavioural pattern to another, or prevent

such a switch taking place, should it be present in

sufficient concentrations.

4 DEFINING AND

EXPERIMENTING WITH A

REAL-WORLD USE CASE

4.1 Deriving the Scenario

Gunzinger’s work represented an attempt to assess

whether the ant algorithm could be used for real-

world navigation scenarios. What it clearly showed

was that ant type algorithms are wildly inefficient if

the environment is even only partially known. On

this insight it is possible to narrow down the purpose

of an autonomous search by a robot to the case when

a known route is blocked and a second or third

passable route must be found. Formally this problem

can be expressed as the robot knowing a route at

time t0 which is invalid at time t1, discovered by the

robot to be invalid at time t2 and that a new route is

discovered by the robot at time t3 with t0 < t1 < t2 <

t3. The optimisation an ant routing algorithm can

achieve is by directing the following robot to the

correct route without it going through the discovery

phase already performed by its predecessor.

4.2 Deriving the Use Case

Landhuis and Terwellen’s work (2010), which

attempted precisely this, plays an important part in

the development of this papers argument. Based on

the premise that mobile robots making deliveries on

known routes may be blocked for periods of time

long enough for it to be more efficient for the robot

to spend its time searching for a new route, the work

also presumed that the robot would be given tasks,

and a route, by a job server but would not have

continuous contact with the job server via a house-

intern WLAN network and therefore requires partial

autonomy. Given a set of RFID tags which, being

cheaper by far than a WLAN access point and can

be spread redundantly across the corridors of a

building, can be used to store pheromones, a robot

searching for a new route can deposit re-

enforcement or detractor pheromones depending on

whether it is tracing or re-tracing its tracks. Whilst

Gunzinger (and Payton) had to invent pheromone

types to fulfil their respective tasks – and hence

severely compromise the quality of their

conclusions, Landhuis was able to call on the

precedent of the Pharaohs Ant (Robinson, 2008)

which, unlike other ant species, deposits detractor

pheromones to cancel out re-enforcement

pheromones. Given the scenario that the robot used a

local, non recognising, navigation (in this case

ultrasound transducers) and an extended Braitenberg

architecture (Lambrinos, 1995) with three active

inputs, the job/map, the local navigation and the

pheromones, Landhuis and Terwellen were able to

show that in the case of a blockage in the parcours

the use of pheromones was not inefficient with

respect to a robot always connected to a server or

one which returned to base when faced with a

blockage. Landhuis and Terwellen were also able to

show that using pheromones to mark routes brought

efficiencies with respect to using random walk

methods.

Figure 1: Simulation results for a robot's response to a

blockage. On job 3 a robot responds to a blockage by

either returning to base (red), or finding another route with

the help of RFID pheromones (green). The blue line shows

the response if the robot is always connected to a server.

Most importantly however Landhuis and

Terwellen were able to show that pheromones and

anonymous local navigation are not sufficient to

avoid positive feedback loops. They therefore

conceived their pheromone to include a direction

and destination factor, on the basis that the set of

active robots were not necessarily following the

same trail and that pheromone deposit on corridor

corners could otherwise be misleading. Equally it

may be asserted that a functioning local navigation

system should have noticed the robot was running

around in circles and judicious placement of RFID

tags, or some clever tag manipulation, may have

helped alleviate the need for the direction

component. The pheromone itself was represented

by the obligatory time-degrading signed integer

TOWARDS A COMMON UNDERSTANDING OF THE DIGITAL PHEROMONE

179

representing concentration and thus represents the

closest attempt so far to emulate a natural

pheromone.

Figure 2: Response times to a blockage (Job 3) given

random walk (red) or pheromones (gblue) or increased

density of RFID tags (green).

4.3 Results Analysis

It’s difficult to conceive of search and rescue

operations using tens hundreds of microbots as a

viable use-case let alone one requiring pheromones.

A trail finding application in a known environment

where short term obstacles can occur – hospitals,

manufacturing plants, warehouses etc spring readily

to mind – does sound like a viable use case and can

be shown to have some merit.

Landhuis and Terwellen show that it is possible

– given adherence to a fundamentalist view of

pheromones – to create a viable application for the

industrial arena that functions whilst retaining their

essential characteristics – which is, or should be, the

reason their emulation was chosen for an application

in the first place. In contrast Payton’s, and others,

rather lackadaisical interpretation of communication

theory in general and pheromones in particular,

serves only to mask the potential this

communication methodology possesses.

5 CONCLUSIONS

Even more dangerous by far is the ad-hock

modification or invention of further pheromone

properties which serves in practice to get something

to work but in fact only serves to mask conceptual

failings in the implementation of the research work.

The first failing is not to realise that it has not been

proven that a bio-property can be abstracted out of

its natural eco-system and transplanted into some

arbitrary technical solution. The refusal to consider

or acknowledge this failure results in

implementations of bio-inspired properties are

condemned to endless research cycles of abstracted

refinement, usually totally ignoring the fact that this

particular property resulted from generations of

embodied refinement in the first place. In short there

exists a serious methodological issue with which

much of research is conducted in this area which,

whilst touched on by previous literature (Pfeiffer

1999), needs to be better acknowledged in future.

Current natural science understanding of

pheromones tends to categorise them by the

behaviours they trigger. Current technical

understanding categorises them under

communication methods. The two don’t fit. The

triggering of a behavioural pattern is deeply

connected with the control architecture of the robot,

itself a subject where the jury is still in consideration

(Gershenson, 2005

). Whilst researchers using close-

to-life pheromones (gas, light) implicitly

acknowledge this through the limitations their

medium imposes on them others don’t and therefore

spend research time chasing issues that would have

been better avoided by an appreciation of this inter-

connectivity.

There appears to be an unfortunate element of

chance regarding the technicalisation of bio-inspired

properties. From a methodological point of view a

behaviour was specified and a bio-inspired tool was

found, it could equally have been that Landhuis and

Terwellen remained ignorant of the existence of the

Pharaohs ant and hence could have invented some

message passing system that functioned more or less

as well, in their case the increased robustness of the

bio-inspiredness of the solution has not been proven

but its relative simplicity certainly has.

Therefore it might be worth investigating the

creation of a list of biological behavioural patterns

so that technical researchers can better visualise

what kind of beast they wish to emulate and more

importantly what kind of sensor and actuators are

required. There is of course a sizeable ethical

dimension to building one’s own beast out of a

collection of behaviours like some modern day Dr.

Frankenstein and, given that scientific method seeks

to establish boundary conditions and work inwards

to the solution core, a new methodology must be

established to ensure that the behavioural patterns do

not express themselves all too negatively given some

hitherto unknown and unfortunate set of input

values.

In conclusion we would like to see a better

theoretical appreciation or possibly formal definition

of pheromones possibly based on the general rules

asserted earlier in the paper on which technical

researcher can base their work on and so better

understand their advantages and disadvantages.

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REFERENCES

Bongard, J., Zykov, V., Lipson, H. 2006. Resilient

machines through continuous self-modeling. Science,

314: 1118-1121.

Borzelloi, E., Merkle, L. D., 2005. Multi-Robot

Cooperation Using the Ant Algorithm with Variable

Pheromone Placement. In: Proc. IEEE Congress on

Evolutionary Computation.

Campo A, Gutiérrez A, Nouyan S, Pinciroli C,

Longchamp V, Garnier S, Dorigo M. 2010. Artificial

pheromone for path selection by a foraging swarm of

robots. In: Biological Cybernetics. Nov;103(5):339-

52. Nov. 2010.

Gershenson, C., 2005. Cognitive paradigms: which one is

the best? In: Cognitive Systems Research. Volume 5,

Issue 2, June 2004, Pages 135-156.

Doran, H., D. 2009a A Communication Technique for

Swarm-Capable Autonomous Agents. In: Proceedings

of Second International Conference on Robot

Communication and Coordination:

Doran, H. D., Meli, M. 2009b Verbesserung autonomer

Roboternavigation mit RFID basierten Pheromonen.

In Tagungsband 11th Wireless Technologies

Kongress. - Stuttgart: VDE,

Ducatelli, F., DeCaro, G.A., Gambdradella, L.M. 2008.

Robot Navigation in a Networked Swarm. In: Proc.

First International Conference on Intelligent Robotics

and Applications. Berlin.

Dünner, S., Kern, D., 2008. Ethernet POWERLINK as a

Communication System Internal to and Between

Autonomous Agents. In Proc. IEEE International

Symposium on Industrial Electronics.

Fujisawa, R., Imamura, H., Hashimoto, T., Matsuno, F.

2008. Communication Using Pheromone Field for

Multiple Robots, In: Proc. IEEE/RSJ International

Conference on Intelligent Robots and Systems.

Gershenson, C., 2005. Cognitive paradigms: which one is

the best? In Cognitive Systems Research. Volume 5,

Issue 2, June 2004, Pages 135-156.

Gunzinger, D., Pfiffner, S. 2008. How to Motivate a

Robot. Diploma Thesis. Zürich University of Applied

Sciences. Unpublished.

Herianto,K. D. 2009 Realization of an artificial

pheromone system in random data carriers using RFID

tags for autonomous navigation. In: Proc. IEEE

International Conference on Robotics and

Automation.

Kuwana, Y. Shimoyama, I. Miura, H. 1995, Steering

control of a mobile robot using insect antennae. In:

Proc. IEEE Int. Con. Intelligent Robots and Systems

95. 'Human Robot Interaction and Cooperative

Robots', Proceedings. 1995.

Lambrinos, D., Scheir, C., 1995. Extended Braitenberg

Architectures.http://www8.cs.umu.se/kurser/TDBD17/

VT04/dl/Assignment%20Papers/Extended%20Braiten

berg%20Architectures.pdf Last viewed March 2011.

Landhuis, P., Terwellen, C., 2010 Navigation by Nose:

Implementing Pheromone Communication for

Autonomous Mobile Navigation Applications.

Navigation. BA Thesis. Zürich University of Applied

Sciences , Saxion University of Applied Sciences.

Unpublished.

Lichtensteiger, L., 2005 Bodies that think quickly and

learn fast: on the interdependence of morphology and

control for intelligent behaviour. Shaker, Aachen

Mayet, R., Roberz, J., Schmickl, T., Crailsheim K., 2010.

Antbots: A Feasible Visual Emulation of Pheromone

Trails for Swarm Robots. In: Proc. 7th international

conference on Swarm intelligence. Springer, Berlin.

Mamei, M. Zambonelli, F. 2005. Physical deployment of

digital pheromones through RFID technology. In:

Proc. IEEE Swarm Intelligence Symposium.

Meng, Y. 2008 Q-Learning Adjusted Bio-Inspired Multi-

Robot Coordination. In: Lazinica , A. (Ed.) Recent

Advances in Multi-Robot Systems, pp. 139-152, May

2008. I-Tech Education and Publishing, Vienna,

Austria.

Payton, D., Daly, M, Estkowski, R., Howard, R., Lee, C.

2001. Pheromone robotics. Autonomous Robots,

11(3):319-324, Nov. 2001.

Payton, D. Estkowski, R., Howard, R., 2003 Compound

Behaviors in Pheromone Robotics, Robotics and

Autonomous Systems, 44 (3-4): 229-240, Sept. 2003.

Payton, D., Estkowski, R, Howard, M. 2004. Pheromone

Robotics and the Logic of Virtual Pheromones. In:

Swarm Robotics. SAB 2004 International Workshop

LNCS 3342, Springer, New York.

Pfeiffer, R. Scheier, C. 1999 Understanding Intelligence.

MIT Press, Cambridge, MA.

Purnamadjaja, A. H. Russell, R. A. 2004. Pheromone

communication: implementation of necrophoric bee

behaviour in a robot swarm. In: Proc. IEEE

Conference on Robotics, Automation and

Mechatronics,

Reinhart, J., Sirnivasn, M., V., 2009 The Role of Scents in

Honey Bee Foraging and Recruitment. In Jarau, S.,

Hrncir, M. (Eds) Food Exploitation by Social Insects.

Ecological Behavioural and Theoretical Approaches.

CRC Press.

Robinson, E. J. H., Ratnieks, F. L. W., Holcombe, M..

(2008) An agent-based model to investigate the roles

of attractive and repel-lent pheromones in ant decision

making during foraging. In: Journal of Theoretical

Biology, Vol. 255, 2008, pp.250-258.

Susnea, I. Vasiliu, G. Filipescu, A. Serbencu, A.

Radaschin, A. 2009. Virtual pheromones to control

mobile robots. A neural network approach. In: Proc.

IEEE International Conference on Automation and

Logistics. ICAL '09.

Svennebring, J., Koenig, S. 2004. Building Terrain

Covering Ant Robots: a Feasibility Study,

Autonomous Robots, 16 (3): 313-332, May 2004.

Nicholas R. Hoff, N.R., Sagoff, A., Wood, R.J., Nagpal,

R., 2010. Two Foraging Algorithms for Robot Swarms

Using Only Local Communication. In: Proc IEEE Int.

Conf. on Robotics and Biomimetics, Tianjin, China.

Wyatt, T.D. 2003 . Pheromones and animal behaviour,

communication by smell and taste. Cambridge

University Press.

TOWARDS A COMMON UNDERSTANDING OF THE DIGITAL PHEROMONE

181