58
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Robotic communication with ants

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          ABSTRACT

          We used a robotic gantry to test the hypothesis that tandem running in the ant Temnothorax albipennis can be successful in the absence of trail laying by the leader . Pheromone glands were placed on a pin attached to a gantry. This set-up substituted for the leader of a tandem run. Neither the pin nor the glands touched the substrate and thus the ant following the robot was tracking a plume of airborne pheromones. The robot led individual workers from their current nest to a potential new one. The robotic gantry was programmed to allow for human intervention along its path to permit the following ant to stop and survey its surroundings and then catch up with its mechanical leader. The gantry then automatically tracked the precise route taken by each ant from the new nest back to the old one. Ants led by the robot were significantly more successful at finding their way home than those we carried to the new nest that had no opportunity to learn landmarks. The robot was programmed to take either a straight or a sinusoidal path to the new nest. However, we found no significant difference in the abilities of ants that had been led on such direct or sinuous paths to find their way home. Here, the robot laid no trail but our findings suggest that, under such circumstances, the following ant may lay a trail to substitute for the missing one.

          Abstract

          Highlighted Article: During tandem running, a leading ant teaches a follower the route to a resource. Key features of real tandem runs were successfully reproduced using a gantry as a robotic leader.

          Related collections

          Most cited references49

          • Record: found
          • Abstract: found
          • Book: not found

          The Ants

          From the Arctic to South Africa - one finds them everywhere: Ants. Making up nearly 15% of the entire terrestrial animal biomass, ants are impressive not only in quantitative terms, they also fascinate by their highly organized and complex social system. Their caste system, the division of labor, the origin of altruistic behavior and the complex forms of chemical communication makes them the most interesting group of social organisms and the main subject for sociobiologists. Not least is their ecological importance: Ants are the premier soil turners, channelers of energy and dominatrices of the insect fauna. TOC:The importance of ants.- Classification and origins.- The colony life cycle.- Altruism and the origin of the worker caste.- Colony odor and kin recognition.- Queen numbers and domination.- Communication.- Caste and division of labor.- Social homeostasis and flexibility.- Foraging and territorial strategies.- The organization of species communities.- Symbioses among ant species.- Symbioses with other animals.- Interaction with plants.- The specialized predators.- The army ants.- The fungus growers.- The harvesters.- The weaver ants.- Collecting and culturing ants.- Glossary.- Bibliography.- Index.
            Bookmark
            • Record: found
            • Abstract: found
            • Book: not found

            Modeling Survival Data: Extending the Cox Model

            This is a book for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Its goal is to extend the toolkit beyond the basic triad provided by most statistical packages: the Kaplan-Meier estimator, log-rank test, and Cox regression model. Building on recent developments motivated by counting process and martingale theory, it shows the reader how to extend the Cox model to analyse multiple/correlated event data using marginal and random effects (frailty) models. It covers the use of residuals and diagnostic plots to identify influential or outlying observations, assess proportional hazards and examine other aspects of goodness of fit. Other topics include time-dependent covariates and strata, discontinuous intervals of risk, multiple time scales, smoothing and regression splines, and the computation of expected survival curves. A knowledge of counting processes and martingales is not assumed as the early chapters provide an introduction to this area. The focus of the book is on actual data examples, the analysis and interpretation of the results, and computation. The methods are now readily available in SAS and S-Plus and this book gives a hands-on introduction, showing how to implement them in both packages, with worked examples for many data sets. The authors call on their extensive experience and give practical advice, including pitfalls to be avoided. Terry Therneau is Head of the Section of Biostatistics, Mayo Clinic, Rochester, Minnesota. He is actively involved in medical consulting, with emphasis in the areas of chronic liver disease, physical medicine, hematology, and laboratory medicine, and is an author on numerous papers in medical and statistical journals. He wrote two of the original SAS procedures for survival analysis (coxregr and survtest), as well as the majority of the S-Plus survival functions. Patricia Grambsch is Associate Professor in the Division of Biostatistics, School of Public Health, University of Minnesota. She has collaborated extensively with physicians and public health researchers in chronic liver disease, cancer prevention, hypertension clinical trials and psychiatric research. She is a fellow the American Statistical Association and the author of many papers in medical and statistical journals.
              Bookmark
              • Record: found
              • Abstract: found
              • Book: not found

              Modeling Survival Data: Extending the Cox Model

              This is a book for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Its goal is to extend the toolkit beyond the basic triad provided by most statistical packages: the Kaplan-Meier estimator, log-rank test, and Cox regression model. Building on recent developments motivated by counting process and martingale theory, it shows the reader how to extend the Cox model to analyse multiple/correlated event data using marginal and random effects (frailty) models. It covers the use of residuals and diagnostic plots to identify influential or outlying observations, assess proportional hazards and examine other aspects of goodness of fit. Other topics include time-dependent covariates and strata, discontinuous intervals of risk, multiple time scales, smoothing and regression splines, and the computation of expected survival curves. A knowledge of counting processes and martingales is not assumed as the early chapters provide an introduction to this area. The focus of the book is on actual data examples, the analysis and interpretation of the results, and computation. The methods are now readily available in SAS and S-Plus and this book gives a hands-on introduction, showing how to implement them in both packages, with worked examples for many data sets. The authors call on their extensive experience and give practical advice, including pitfalls to be avoided. Terry Therneau is Head of the Section of Biostatistics, Mayo Clinic, Rochester, Minnesota. He is actively involved in medical consulting, with emphasis in the areas of chronic liver disease, physical medicine, hematology, and laboratory medicine, and is an author on numerous papers in medical and statistical journals. He wrote two of the original SAS procedures for survival analysis (coxregr and survtest), as well as the majority of the S-Plus survival functions. Patricia Grambsch is Associate Professor in the Division of Biostatistics, School of Public Health, University of Minnesota. She has collaborated extensively with physicians and public health researchers in chronic liver disease, cancer prevention, hypertension clinical trials and psychiatric research. She is a fellow the American Statistical Association and the author of many papers in medical and statistical journals.
                Bookmark

                Author and article information

                Journal
                J Exp Biol
                J Exp Biol
                JEB
                jexbio
                The Journal of Experimental Biology
                The Company of Biologists Ltd
                0022-0949
                1477-9145
                1 August 2022
                9 August 2022
                9 August 2022
                : 225
                : 15
                : jeb244106
                Affiliations
                [1 ]School of Biological Sciences, University of Bristol , 24 Tyndall Avenue, Bristol BS8 1TQ, UK
                [2 ]Department of Biology, University of York , Wentworth Way, York YO10 5DD, UK
                Author notes
                [* ]Author for correspondence ( nigel.franks@ 123456bristol.ac.uk )
                Author information
                http://orcid.org/0000-0001-8139-9604
                http://orcid.org/0000-0002-9443-6336
                http://orcid.org/0000-0002-3270-8746
                http://orcid.org/0000-0002-7734-7841
                http://orcid.org/0000-0001-9300-6986
                Article
                JEB244106
                10.1242/jeb.244106
                9440752
                35942527
                d9e9d054-8391-4d5c-95fd-8d138536b6e5
                © 2022. Published by The Company of Biologists Ltd

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                History
                : 7 February 2022
                : 4 July 2022
                Funding
                Funded by: University of Bristol, http://dx.doi.org/10.13039/501100000883;
                Funded by: University of Bristol, http://dx.doi.org/10.13039/501100000883;
                Categories
                Research Article

                Molecular biology
                animal–robot interaction,pheromones,tandem running,social behaviour,learning,orientation

                Comments

                Comment on this article

                scite_
                0
                0
                0
                0
                Smart Citations
                0
                0
                0
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content168

                Cited by4

                Most referenced authors373