C.1 Source Acquisition

C.1 Source Acquisition

Overview

I chose to explore the field of swarm robotics. This fascinating field seeks to determine methods of getting multiple robots to "think" and work together to solve problems.

The overarching question I posed was: “How do large groups of animals communicate? How can researchers apply biologically inspired methods of communication to solve the problem of controlling swarms of multiple robots?”

C.1.0) Source

To address the requirement "Identify one recent paper …. Cite it appropriately, using the References format found in the Wiki.", I chose to use reference [1].

This paper is concerned with the self-organization of multiple robots. The goal of the research was to investigate methods of autonomous control that are inspired by the natural world, as seen by this quote from the paper's abstract:

Taking inspiration from insect societies, we present an experimental study of self-organising behaviours for a group of robots, which exploit communication to coordinate their activities.

The article went on to define several different forms of communication found in the insect world. I have copied these definitions verbatim below.

Indirect or stigmergic communication-
A form of communication that takes place through the environment, as a result of the actions performed by some individuals, which indirectly influence someone else’s behaviour (e.g. pheromone trails).
Direct interaction-
A form of communication that implies a non-mediated transmission of information, as a result of the actions performed by some individuals, which directly influence someone else’s behaviour (e.g. antennation, mandibular pulling).
Direct communication-
A form of communication that implies a non-mediated transmission of information, without the need of any physical interaction (e.g. the waggle dance, stridulations).

I found these different methods of communication fascinating. Thus, the remainder of my sources will be further investigations into biologically inspired methods of controlling swarms of robots.

C.1.1) Venue

Below is evidence that reference [1] is a credible source and worthy of being used to complete this assignment.

Article Citations

As of 01/25/2011, reference [1] has the following number citations according to these scholarly databases:

Impact Factor

According to ISI Journal Citation Report, the journal "Biological Cybernetics" has an impact factor of 1.697. It is ranked 8th out of the 19 journals in the category of COMPUTER SCIENCE, CYBERNETICS.

This journal is ranked as 0.160 by Scopus Journal Analyzer.

C.1.2) Authors' Qualifications

The first author of the article, Dr. Vito Trianni, has a Scopus-computed h index of 9. Dr. Trianni a researcher at the Institute of Cognitive Sciences and Technologies (ISTC) of the Italian National Research Council (CNR). The principle investigator, Dr. Marco Dorigo, has a h index of 28. Dr. Dorigo is research director for the Belgian Fonds de la Recherche Scientifique and is research director of the IRIDIA lab at the Université Libre de Bruxelles.

C.1.3) Source Identification Methods

When I first contacted our librarian, Doug McGee, I had a completely different set of articles in mind. My main article was simply a general review article about swarm robotics. It went over the basics of swarm robotics, and touched on some areas of research, but it was not very specific. Similarly, some of the other articles I had found were basic reviews. I showed these to Mr. McGee, along with information about the citation rates for these articles found via Scopus, ISI Web of Science, and Google Scholar. A brief snippet of Mr. McGee's reply is shown below:

Have you been able to identify a particular aspect of swarm robotics of interest to you? Looks like two of your articles deal with communication in particular. Once you can identify more precisely what you're looking for, you can proceed from overview literature to more research oriented papers on that particular topic.

I thought I was was done the project, but Mr. McGee pointed out (and rightfully so) that three of my articles (references [2], [3], and [4]) were just general overviews. While these articles did not prove to be helpful for satisfying this assignment, they did provide some interesting background reading, and I do not regret the time I invested in reading them.

Heeding Mr. McGee's advice, I decided to drop the three general articles, and keep the two about communications. I then went back to the scholarly databases, and started looking for articles that dealt with applications of bio-inspired robots for the control of swarm robots.

After my consultation with Mr. McGee, I was able to narrow down my topic and hone in on the aspect of swarm technology that most interested me.

C.1.4) High Quality Bioinspired Robotics Contribution

Confident that [1] is a relevant article, authored by reputable researchers, and published in a well-regarded journal, the below quote from the body of the article illustrates the lessons that can be learned from insect's self-organization techniques, and the values of self-organization to robotic systems:

Self-organisation is often observed in biology, and in particular in many animal societies, not limited to social insects like ants, bees or termites (Camazine et al. 2001). From an engineering perspective, there are multiple advantages in designing a self-organising system.

C.1.5) General Robotics Literature

Checking Claims via Two Quality Sources

General Robotics Source 1

Reference [5] discusses the following study:

In this experimental study, we show collective decision-making by mixed groups of cockroaches and socially integrated autonomous robots, leading to shared shelter selection. Individuals, natural or artificial, are perceived as equivalent, and the collective decision emerges from nonlinear feedbacks based on local interactions.

By mimicking the communication methods of cockroaches, robots were able to perform collective decision-making among themselves and the cockroaches.

Quality of Robotics Source 1

As of 01/25/2011, reference [5] has the following number citations according to these scholarly databases:

The first author of this paper, Dr. José Halloy, has a Scopus h index of 12. The principle investigator of this paper, Dr. Jean Louis Deneubourg, is a professor and senior researcher at Université libre de Bruxelles, and has a Scopus h index of 26.

In terms of the credibility of the venue, according to ISI Journal Citation Report, the journal "Science" has an impact factor of 29.747, making its rank 2nd out of 50 journals in the category of Multidisciplinary Sciences.

This journal is ranked as 4.777 by Scopus Journal Analyzer.

General Robotics Source 2

Reference [6] draws its inspiration from the foraging habits of ants, as seen in this quote from the article's abstract:

In this article, we analyze the behavior of a group of robots involved in an object retrieval task. The robots’ control system is inspired by a model of ants’ foraging.

When an ant discovers a tasty morsel that it would like to bring back to its colony, but is too big for it to carry on its own, the ant will contact fellow ants and enlist them to help carry the food. The researchers were able to create a control system for a group of robots based on the same principles that ants demonstrate, whereby when a robot encounters an object that it needs to move, but is too large, the robot will get other robots to come to its aid.

Quality of Robotics Source 2

As of 01/25/2011, reference [6] has the following number citations according to these scholarly databases:

The first author of this paper, Dr. Thomas Halva Labella, has a Scopus h index of 6. The primary investigator, Dr. Jean Louis Deneubourg, has a Scopus h index of 26.

Note: I realize that [5] and [6] have the same principle investigator. However, [5] was published a year after [6], and while [6] had only 3 authors, [5] had 16 authors. Also, while the two articles both deal with swarm robotics, the first involves studying communication between cockroaches, while the second involves researching communications between ants. On top of all this, the articles were published in two different, peer reviewed journals, with one journal being focused on general science, and the other specifically on robotics. Taking all these factors into account, I felt these articles represented a diversity in author credentials and subject matter. Thus, I felt confident that the papers were different enough to warrant counting them as two different sources.

In terms of the credibility of the venue, according to ISI Journal Citation Report, the journal "ACM Transactions on Autonomous and Adaptive System" has an impact factor of 1.364, making its rank 28th out of 92 journals in the category of THEORY & METHODS.

This journal is ranked as 0.074 by Scopus Journal Analyzer.

Additional Sources

The below sources are less cited and from less mainstream journals, and thus I did not think they warranted being my primary sources. However, I found the research that they are performing involving olfactory sensors and synthetic pheromones to be incredibly fascinating. I believe that as more and more research is done on this interesting subset of biologically inspired robotic communication, sources such as these will gain more credibility.

Relevant Research at Penn

Dr. Vijay Kumar is doing some incredible research into swarm technology here at Penn. Unfortunately, while Professor Kumar has a very high Scopus h index of 38 the majority of his papers on swarm intelligence have not been cited many times. That being said, I found reference [(7)] to be highly interesting. As demonstrated by the below excerpt from its abstract, Dr. Kumar's lab is doing some very interesting work in the field of bio-inspired communication:

We present a biologically inspired approach to the dynamic assignment and reassignment of a homogeneous swarm of robots to multiple locations, which is relevant to applications like search and rescue, environmental monitoring, and task allocation. Our work is inspired by experimental studies of ant house hunting and empirical models that predict the behavior of the colony that is faced with a choice between multiple candidate nests.

Additional Robotics Source 1

Reference [8] is a very interesting article written by a pair of researchers from Australia. Their research draws inspiration from the common honeybee. The content of this article can be succinctly summarized by a quote from its abstract:

The necrophoric pheromone released by dead bees triggers corpse removal behaviour in passing worker bees. In the context of a robot swarm one of the proposed applications for this behaviour is to locate and rescue disabled robots that release a pheromone as a form of distress signal.

Quality of Additional Robotics Source 1

As of 01/25/2011, reference [8] has the following number citations according to these scholarly databases:

According to ISI Journal Citation Report, the journal "Robotica" (the journal from which reference [8] was taken) has an impact factor of 0.992. It is ranked 11th out of the 16 journals in the category of Robotics.

This journal is ranked as 0.045 by Scopus Journal Analyzer.

Additional Robotics Source 2

Reference [9] was written by a group of researchers from the University of Minnesota who are attempting to use biologically inspired communication techniques to control swarms of robots that are meant to survey disaster zones and aid rescue workers in the task of locating victims. In order to have the robots "fan out" and thoroughly survey the disaster zone, the researchers used techniques culled from insects:

Using the concept of ‘repellent virtual pheromones’ inspired by insect colony coordination behaviors, miniature robots can be quickly dispersed to survey a disaster site.

Quality of Additional Robotics Source 2

As of 01/25/2011, reference [9] has the following number citations according to these scholarly databases:

According to ISI Journal Citation Report, "The Journal of Intelligent and Robotic Systems" (the journal from which reference [9] was taken) has an impact factor of 0.858. It is ranked 13th out of the 16 journals in the category of Robotics.

This journal is ranked as 0.047 by Scopus Journal Analyzer.

C.1.6) Biology Literature

Generating More Evidence from the Biological Literature

Biological Source 1

The abstract of reference [10] states:

This study generates predictions about the evolutionary conditions conducive to the emergence of communication and provides guidelines for designing artificial evolutionary systems displaying spontaneous communication.

To generate these predictions, the researchers:

…conducted repeated trials of experimental evolution with robots that could produce visual signals to provide information on food location.

One of the conclusions stated in the body of this article is:

This study demonstrates that sophisticated forms of communication including cooperative communication and deceptive signaling can evolve in groups of robots with simple neural networks.

What made this article so interesting was the fact that not only did the robots use cooperative communication which was inspired by insect colonies (as stated in the body), but the researchers demonstrated that such communication systems could evolve from robots with simple neural networks.

Quality of Biological Source 1

As of 01/25/2011, reference [10] has the following number citations according to these scholarly databases:

The first author of this paper, Dr. Dario Floreano, director of the Laboratory of Intelligent Systems (LIS) at the École Polytechnique Fédérale de Lausanne in Switzerland, has a Scopus h index of 19. The principle investigator of this paper, Dr. Laurent Keller, a Full Professor of Evolutionary Ecology and the Head of the Department of Ecology and Evolution at the University of Lausanne, has a Scopus h index of 37.

In terms of the credibility of the venue, according to ISI Journal Citation Report, the journal "Current Biology" has an impact factor of 10.992, making its rank 15th out of 283 journals in the category of Biochemistry and Molecular Biology.

This journal is ranked as 3.001 by Scopus Journal Analyzer.

Biological Source 2

Reference [11] is an article about what we can learn from the pheromone receptors on moths.

To quote the researcher's abstract, the results presented in this paper:

…should stimulate further quantitative studies on the evolutionary adaptation of olfactory nervous systems to odorant plumes and on the plume characteristics that are most informative for the ‘sniffer’. Both aspects are relevant to the design of olfactory sensors for odour-tracking robots.

This paper studied what effects changes to the properties of a pheromone cloud would have on its detection by the pheromone receptor neuron of the male moth Antheraea polyphemus. Their goal, as stated above, was to then apply this knowledge to creating better olfactory sensors for robots to use in odor detection and interpretation for applications such as tracking and olfactory communication.

Quality of Biological Source 2

As of 01/25/2011, reference [11] has the following number citations according to these scholarly databases:

The first author of this paper, Dr. Lubomir Kostal, has a Scopus h index of 5. The second author of this paper, Dr. Petr Lansky, has a Scopus h index of 14. The principle investigator, Dr. Jean Pierre Rospars, Research Director at National Institute for Agricultural Research (INRA), France, has a Scopus h index of 12.

In terms of the credibility of the venue, according to ISI Journal Citation Report, the journal "PLoS Computational Biology" has an impact factor of 5.759, making its rank 1st out of 29 journals in the category of MATHEMATICAL & COMPUTATIONAL BIOLOGY.

This journal is ranked as 0.807 by Scopus Journal Analyzer.

I realize that this source might not have been cited as many times as my other articles. However, it comes from the number one journal in the field of mathematical and computational biology, and thus I felt it was still a very credible paper.

Additional Biological Source 1

In my quest to find articles for this assignment, I stumbled across several that, while interesting, were not exactly what I was looking for. However, I did find one that, while not about robotics, was very applicable to my area of interest. Several of my articles dealt with olfactory communication using pheromones, and possible applications for robotics. Reference [12] studies communication in a certain type of honeybees. While we know from earlier articles (see [6]) that many insects communicate using pheromones, this article presents evidence that when performing certain tasks (such as changing a nest site), pheromones are not practical for communication, and insects must rely on other means of communication (for instance, visual cues).

The hypothesis tested, as stated in the abstract:

The first proposes that the flying scouts streak through the swarm cloud in the direction of the goal, thereby indicating the travel direction visually (vision hypothesis). The second proposes that flying scouts release pheromones from their Nasanov glands at the front of the cloud of flying bees, thereby indicating the travel direction chemically (olfaction hypothesis).

The results of the experiment showed that when moving nest sites, bees rely on visual communication, and not pheromones. The reason why I found this so interesting is that similar thought processes must be applied to researching biologically inspired methods of communications for swarms of robots. This biological paper showed that there is no communication panacea, and in order for robots to communicate effectively in different environments and situations, we must realize that instead of using just one method of communication, we must be able to combine multiple types of communication to ensure the creation of a robust, adaptable system.

Quality of Additional Biological Source 1

As of 01/25/2011, reference [12] has the following number citations according to these scholarly databases:

The first author of this paper, Dr. Madeleine Beekman, has a Scopus h index of 17. The second author of this paper, Dr. Robert L. Fathke, has a Scopus h index of 2. The principle investigator, Dr. Thomas Dyers Seeley, has a Scopus h index of 22.

In terms of the credibility of the venue, according to ISI Journal Citation Report, the journal "Animal Behaviour" has an impact factor of 2.890, making its rank 7th out of 129 journals in the category of Zoology.

This journal is ranked as 0.208 by Scopus Journal Analyzer.

References

1. Trianni, V., & Dorigo, M. Self-organisation and communication in groups of simulated and physical robots. Biological Cybernetics, 95(3), 213-231, 2006.
2. Pfeifer, R., Lungarella, M., & Iida, F. Self-organization, embodiment, and biologically inspired robotics. Science, 318(5853), 1088-1093, 2007.
3. Mondada, F., Gambardella, L. M., Floreano, D., Nolfi, S., Deneubourg, J. -., & Dorigo, M The cooperation of swarm-bots: Physical interactions in collective robotics. IEEE Robotics and Automation Magazine, 12(2), 21-28, 2005.
4. Groß, R., Bonani, M., Mondada, F., & Dorigo, M. Autonomous self-assembly in swarm-bots. IEEE Transactions on Robotics, 22(6), 1115-1130, 2006.
5. Halloy, J., Sempo, G., Caprari, G., Rivault, C., Asadpour, M., Tâche, F., et al. Social integration of robots into groups of cockroaches to control self-organized choices. Science, 318(5853), 1155-1158, 2007.
6. Labella, T. H., Dorigo, M., & Deneubourg, J. Division of labor in a group of robots inspired by ants' foraging behavior. ACM Transactions on Autonomous and Adaptive Systems, 1(1), 4-25, 2006.
7. Hsieh, M. A., Halász, Á, Berman, S., & Kumar, V. Biologically inspired redistribution of a swarm of robots among multiple sites. Swarm Intelligence, 2(2-4), 121-141, 2008.
8. Purnamadjaja, A. H., & Russell, R. A. Pheromone communication in a robot swarm: Necrophoric bee behaviour and its replication. Robotica, 23(6), 731-742, 2005.
9. Pearce, J. L., Powers, B., Hess, C., Rybski, P. E., Stoeter, S. A., & Papanikolopoulos, N. Using virtual pheromones and cameras for dispersing a team of multiple miniature robots. Journal of Intelligent and Robotic Systems: Theory and Applications, 45(4), 307-321, 2006.
10. Floreano, D., Mitri, S., Magnenat, S., & Keller, L. Evolutionary conditions for the emergence of communication in robots. Current Biology, 17(6), 514-519, 2007.
11. Kostal, L., Lansky, P., & Rospars, J. Efficient olfactory coding in the pheromone receptor neuron of a moth. PLoS Computational Biology, 4(4), 2008.
12. Beekman, M., Fathke, R. L., & Seeley, T. D. How does an informed minority of scouts guide a honeybee swarm as it flies to its new home?. Animal Behaviour, 71(1), 161-171, 2006.