[Tweets]

21/05/2018 6:37pm
RT @rodneyabrooks: Hard truths about how hard AI is going to be. Disappointing for the alarmists, perhaps. [LINK]
17/05/2018 12:43pm
A detailed look at 87 citations reported by #GoogleScholar reveals that only 13% of the papers have applied the cit… [LINK]
15/05/2018 7:10pm
RT @elonmusk: @TalkTesla @Techmeme @timkhiggins According to NHTSA, there was an automotive fatality every 86M miles in 2017 (~40,000 death…

[Publications]

Journal papers

Pitonakova, L., Crowder, R. & Bullock, S. (2018). Information exchange design patterns for robot swarm foraging and their application in robot control algorithms. Frontiers in Robotics and AI, DOI: 10.3389/frobt.2018.00047
[download pre-print]
[about the project]

Pitonakova, L., Crowder, R. & Bullock, S. (2018). The Information-Cost-Reward framework for understanding robot swarm foraging. Swarm Intelligence, 12(1), 71-96.
[about the project]

Pitonakova, L., Crowder, R. & Bullock, S. (2016). Information flow principles for plasticity in foraging robot swarms. Swarm Intelligence, 10(1), 33–63.
[about the project]

Wilson, R., zu Erbach-Schoenberg, E., Albert, M., Power, D., Tudge, S., Gonzalez, M., Guthrie, S., Chamberlain, H., Brooks, C., Hughes, C., Pitonakova, L., Buckee, C., Lu, X., Wetter, E., Tatem, A. & Bengtsson, L. (2016). Rapid and near real-time assessments of population displacement using mobile phone data following disasters: The 2015 Nepal earthquake. PLOS Currents Disasters, DOI: 10.1371/currents.dis.d073fbece328e4c39087bc086d694b5c.

Pitonakova, L. (2013). Ultrastable neuroendocrine robot controller. Adaptive Behaviour, 21(1), 47-63.
[about the project]

Conference publications (peer reviewed)

Pitonakova, L., Giuliani, M., Pipe, A., Winfield, A. (in press) Feature and performance comparison of the V-REP, Gazebo and ARGoS robot simulators. Proceedings of the 19th Towards Autonomous Robotic Systems Conference (TAROS 2018), Springer.

Pitonakova, L., Crowder R. & Bullock, S. (2017). Behaviour-Data Relations Modelling Language for multi-robot control algorithms. Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017), IEEE, 727-732.
[about the project]

Pitonakova, L., Crowder R. & Bullock, S. (2016). Task allocation in foraging robot swarms: The Role of Information Sharing. In Gershenson, C. et al. (eds.), Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV), MIT Press, 306-313.
[about the project]

Pitonakova, L., Crowder R. & Bullock, S. (2015). Design Patterns for Swarms of Robot Foragers. Abstract & poster at The International Conference on Intelligent Robots and Systems (IROS 2015), Hamburg, Germany.
[download the poster]

Pitonakova, L., Crowder R. & Bullock, S. (2014). Understanding the role of recruitment in collective robot foraging. In Lipson, H. et al. (eds.), Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14), MIT Press, 264-271.
[about the project]

Pitonakova, L. & Bullock, S. (2013). Controlling ant-based construction. In Lio, P. et al. (eds.), Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems (ECAL 2013), MIT Press, 151-158.
[about the project]

Book chapters

Pitonakova, L. (2014). Afterword: Rise of the Machines. In: Amos, M. & Page, R. (eds.) Beta Life - Stories from an A-life Future. Comma Press, pp. 37-40.

Selected talks

2017: Behaviour-Data Relations Modelling Language For Multi-Robot Control Algorithms: The International Conference on Intelligent Robots and Systems (IROS 2017), Vancouver, Canada

2017: Designing Robot Swarms: a talk at the Southwest Futurists, Bristol.

2016: What is Life?: a talk at the Sceptics Cafe, Brighton.

2016: Task Allocation in Foraging Robot Swarms: The Role of Information Sharing: The Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV)

2015: Object Oriented Software Development (In Python): a talk for members of the Flowminder Foundation and of The World Food Programme.

2015: The Hive Mind game: University of Sussex, 2015

2015: Towards Design Patterns for Robot Swarms: invited talk at the Bristol Robotics Laboratory, Bristol, United Kingdom

2014: Software Project Planning & Management: workshop at 2014 Student Conference in Complexity Science (SCCS 2014)

2014: Understanding the Role of Recruitment in Collective Robot Foraging: The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14)

2013: Controlling Ant-Based Construction: Twelfth European Conference on the Synthesis and Simulation of Living Systems (ECAL 2013)

2013: Information Exchange and Coordination in Robot Swarms: annual Agents, Interaction and Complexity meeting, University of Southampton

Selected posters

2015: Design Patterns for Swarms of Robot Foragers: The International Conference on Intelligent Robots and Systems (IROS 2015), Hamburg, Germany

2015: Self-Organised Regulation of Foraging Traffic in Robotic Swarms: annual Complex Systems DTC meeting, University of Southampton

2014: Understanding the Role of Recruitment in Collective Robot Foraging: annual Complex Systems DTC meeting, University of Southampton

 

pyCreeper

The main purpose of pyCreeper is to wrap tens of lines of python code, required to produce graphs that look good for a publication, into functions. It takes away your need to understand various quirks of matplotlib and gives you back ready-to-use and well-documented code.

Citations count fails to measure the impact of research

Academic career progress is often judged by so-called "h-index", that measures how much your research is being cited. I recently had a detailed look at what exactly the citations, specifically those reported by Google Scholar, amount to. Only a relatively small fraction of the reported citations corresponded to research being applied or reproduced in a meaningful way.

V-REP, Gazebo or ARGoS? A robot simulators comparison

Let’s have a look at three commonly used open-source simulators for robotics: V-REP, Gazebo and ARGoS, to find out which one suits your project the best.

Designing Effective Roadmaps for Robotics Innovation

Automated factories, autonomous delivery drones, self-driving cars: these and similar technologies will soon touch every aspect of our lives. An engaging discussion about how these technologies are regulated and innovated took place at the IROS 2017 conference.

The Information-Cost-Reward framework for understanding robot swarm foraging

The Information-Cost-Reward (ICR) framework relates the way in which robots obtain and share information about where work needs to be done to the swarm’s ability to exploit that information in order to perform work efficiently in the context of a particular task and environment.