Biography
I received the Electronic Engineer degree from the Buenos Aires Institute of Technology (ITBA), Argentina, in 2009. Shortly after, I moved to Swtizerland to join the Distributed Intelligent Systems and Algorithms Laboratory, EPFL, as a research assistant. Since December 2010 I have been working on my PhD thesis on Distributed Adaptation under the supervision of Prof. Alcherio Martinoli.
Research
My thesis is about the automatic design of high-performing robust controllers for mobile robots using exclusively on-board resources. We employ an evaluative approach, where a population-based, on-line machine-learning technique automatically shapes the robots’ behaviors by direct interaction with the real environment. This constitutes an expensive optimization problem as the time needed to evaluate candidate solutions is substantially larger than that required by the metaheuristic operators in the algorithm.
For more details, see the project’s website:
http://disal.epfl.ch/DistributedAdaptation
Publications
2016
Measurements of the Higgs boson production and decay rates and constraints on its couplings from a combined ATLAS and CMS analysis of the LHC pp collision data at $ \sqrt{s}=7 $ and 8 TeV
G. Aad; B. Abbott; J. Abdallah; O. Abdinov; B. Abeloos et al.
Journal of High Energy Physics. 2016-08-05. Vol. 2016, num. 8, p. 45. DOI : 10.1007/JHEP08(2016)045. Noise-Resistant Particle Swarm Optimization for the Learning of Robust Obstacle Avoidance Controllers using a Depth Camera
I. Navarro; E. Di Mario; A. Martinoli
2016. 2016 IEEE Congress on Evolutionary Computation, Vancouver, BC, Canada, July 24-29, 2016. p. 685-692. DOI : 10.1109/CEC.2016.7743859. Distributed Learning of Cooperative Robotic Behaviors using Particle Swarm Optimization
E. L. Di Mario; I. Navarro; A. Martinoli
2016. International Symposium on Experimental Robotics, Marrakech, Morocco, June 15-18, 2014. p. 591–604. DOI : 10.1007/978-3-319-23778-7_39. 2015
Combined Measurement of the Higgs Boson Mass in $pp$ Collisions at $\sqrt{s}=7$ and 8 TeV with the ATLAS and CMS Experiments
G. Aad; B. Abbott; J. Abdallah; O. Abdinov; R. Aben et al.
Physical Review Letters. 2015-05-14. Vol. 114, num. 19, p. 191803. DOI : 10.1103/PhysRevLett.114.191803. Distributed Particle Swarm Optimization – Particle Allocation and Neighborhood Topologies for the Learning of Cooperative Robotic Behaviors
I. Navarro; E. L. Di Mario; A. Martinoli
2015. IEEE/RSJ International Conference on Intelligent Robots and Systems, Hamburg, Germany, September 28 – October 02, 2015. p. 2958-2965. DOI : 10.1109/IROS.2015.7353785. Distributed vs. Centralized Particle Swarm Optimization for Learning Flocking Behaviors
I. Navarro; E. Di Mario; A. Martinoli
2015. 13th European Conference on Artificial Life (ECAL 2015), York, United Kingdom, 20-24 July 2015. p. 302-309. DOI : 10.7551/978-0-262-33027-5-ch056. A Distributed Noise-Resistant Particle Swarm Optimization Algorithm for High-Dimensional Multi-Robot Learning
E. L. Di Mario; I. Navarro; A. Martinoli
2015. IEEE International Conference on Robotics and Automation, Seattle, Washington, USA, May 26-30, 2015. p. 5970-5976. DOI : 10.1109/ICRA.2015.7140036. SwarmViz: An Open-Source Visualization Tool for Particle Swarm Optimization
G. Jornod; E. L. Di Mario; I. Navarro; A. Martinoli
2015. IEEE Congress on Evolutionary Computation, Sendai, Japan, May 25-28, 2015. p. 179-186. DOI : 10.1109/CEC.2015.7256890. Distributed Particle Swarm Optimization using Optimal Computing Budget Allocation for Multi-Robot Learning
E. L. Di Mario; I. Navarro; A. Martinoli
2015. IEEE Congress on Evolutionary Computation, Sendai, Japan, May 25-28 2015. p. 566-572. DOI : 10.1109/CEC.2015.7256940. 2014
Analysis of Fitness Noise in Particle Swarm Optimization: From Robotic Learning to Benchmark Functions
E. L. Di Mario; I. Navarro; A. Martinoli
2014. IEEE Congress on Evolutionary Computation, Beijing, China, July 6-11, 2014. p. 2785-2792. DOI : 10.1109/CEC.2014.6900514. The Role of Environmental and Controller Complexity in the Distributed Optimization of Multi-Robot Obstacle Avoidance
E. Di Mario; I. Navarro; A. Martinoli
2014. IEEE International Conference on Robotics and Automation, Hong Kong, China, May 31 – June 7, 2014. p. 571-577. DOI : 10.1109/ICRA.2014.6906912. Distributed Particle Swarm Optimization for limited-time adaptation with real robots
E. Di Mario; A. Martinoli
Robotica. 2014. Vol. 32, num. 2, p. 193-208. DOI : 10.1017/S026357471300101X. Distributed Particle Swarm Optimization for Limited Time Adaptation in Autonomous Robots
E. Di Mario; A. Martinoli
2014. International Symposium on Distributed Autonomous Robotic Systems, Baltimore, Maryland, USA, November 8-11, 2012. p. 383-396. DOI : 10.1007/978-3-642-55146-8_27. 2013
The Effect of the Environment in the Synthesis of Robotic Controllers: A Case Study in Multi-Robot Obstacle Avoidance using Distributed Particle Swarm Optimization
E. Di Mario; I. Navarro; A. Martinoli
2013. 12th European Conference on Artificial Life, Taormina, Italy, September 2-6, 2013. p. 561-568. DOI : 10.7551/978-0-262-31709-2-ch081. A Comparison of PSO and Reinforcement Learning for Multi-Robot Obstacle Avoidance
E. Di Mario; Z. Talebpour; A. Martinoli
2013. IEEE Congress on Evolutionary Computation, Cancún, México, June 20-23, 2013. p. 149-156. DOI : 10.1109/CEC.2013.6557565. 2011
A Trajectory-based Calibration Method for Stochastic Motion Models
E. Di Mario; G. Mermoud; M. Mastrangeli; A. Martinoli
2011. IEEE/RSJ International Conference on Intelligent Robots and Systems. p. 4341-4347. DOI : 10.1109/IROS.2011.6094940.
