TRAJAN project aims to develop behavioral analysis tools for autonomous agents (pedestrians, mobile robots, cars, animals,…) based on their trajectory. In the first step, we have to classify the different behaviors from a trajectory set. In the second step, the information extracted from the analysis will be used to qualify and quantify a behavior. Thus, in addition to the behavior recognition, we would be able to qualify a behavior (repeatability,…) and in the field of mobile-robot research, this information would help us to optimize the robot controllers leading to the different behaviors.
This project is done in collaboration with the Laboratoire de Production Microtechnique (LPM) .
Team and Collaborators
In collaboration with:
- Jacques Jacot
- Alain Dufaux
This project is founded by the Swiss National Fundation (SNF) grant 200021-105565.
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. 2009
2008
SwisTrack – A Flexible Open Source Tracking Software for Multi-Agent Systems
T. Lochmatter; P. Roduit; C. Cianci; N. Correll; J. Jacot et al.
2008. IEEE/RSJ 2008 International Conference on Intelligent Robots and Systems (IROS 2008), Nice, France, September 22-26, 2008. p. 4004-4010. DOI : 10.1109/IROS.2008.4650937. 2007
A Quantitative Method for Comparing Trajectories of Mobile Robots Using Point Distribution Models
P. Roduit; A. Martinoli; J. Jacot
2007. 2007 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, San Diego, CA, USA, 29 october – 2 november 2007. p. 2441-2448. DOI : 10.1109/IROS.2007.4399126. 2006
Behavioral Analysis of Mobile Robot Trajectories Using a Point Distribution Model
P. Roduit; A. Martinoli; J. Jacot
2006. Ninth Int. Conference on the Simulation of Adaptive Behavior, Roma, 25-29 september. p. 819–830. DOI : 10.1007/11840541_67.
