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)Â .
Team and Collaborators
In collaboration with:
- Jacques Jacot
- Alain Dufaux
Sponsors and Research Period
This project is founded by the Swiss National Fundation (SNF) grant 200021-105565.
Publications
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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
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
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
2016. International Symposium on Experimental Robotics, Marrakech, Morocco, June 15-18, 2014. p. 591â604. 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
Physical Review Letters. 2015-05-14. Vol. 114, num. 19, p. 191803. DOI : 10.1103/PhysRevLett.114.191803.Distributed Multi-Robot Learning using Particle Swarm Optimization
Lausanne, EPFL, 2015.Distributed Particle Swarm Optimization – Particle Allocation and Neighborhood Topologies for the Learning of Cooperative Robotic Behaviors
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
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
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
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
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
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
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
Robotica. 2014. Vol. 32, num. 2, p. 193-208. DOI : 10.1017/S026357471300101X.Distributed Particle Swarm Optimization for Limited Time Adaptation in Autonomous Robots
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
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
2013. IEEE Congress on Evolutionary Computation, CancĂșn, MĂ©xico, June 20-23, 2013. p. 149-156. DOI : 10.1109/CEC.2013.6557565.2011
A Trajectory-based Calibration Method for Stochastic Motion Models
2011. IEEE/RSJ International Conference on Intelligent Robots and Systems. p. 4341-4347. DOI : 10.1109/IROS.2011.6094940.Please note that the publication lists from Infoscience integrated into the EPFL website, lab or people pages are frozen following the launch of the new version of platform. The owners of these pages are invited to recreate their publication list from Infoscience. For any assistance, please consult the Infoscience help or contact support.