Alcherio Martinoli

EPFL ENAC IIE DISAL
GR A2 454 (Bâtiment GR)
Station 2
1015 Lausanne

EPFL ENAC SSIE-GE
GR A2 392 (Bâtiment GR)
Station 2
1015 Lausanne

Expertise

Autonomous Robotics; Distributed Robotics; Swarm Robotics; Distributed Intelligent Systems; Sensor and Actuator Networks; Intelligent Vehicles; Swarm Intelligence; Distributed Control and Estimation; Mechatronic Design; Localization and Navigation

Mission

My research interests focus on methods to design, control, model, localize, and optimize distributed intelligent systems, including multi-robot systems, sensor and actuator networks, and intelligent vehicles. I am also interested in the understanding and control of mixed societies consisting of natural and artificial components. My research policy relies on iteratively closing the loop between theory and physical experiments using model-based and data-driven techniques. Our research output ranges from fundamental, methodological aspects to more applied contributions, often associated with application areas of interest of the ENAC school, especially in environmental and civil engineering.
I received my Diploma in Electrical Engineering from the Swiss Federal Institute of Technology in Zurich (ETHZ), and a Ph.D. in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL). I am currently Full Professor at the School of Architecture, Civil, and Environmental Engineering and the head of the Distributed Intelligent Systems and Algorithms Laboratory. Before joining EPFL I carried out research activities at the Institute of Biomedical Engineering of the ETHZ, at the Institute of Industrial Automation of the Spanish Research Council in Madrid, Spain, and at the California Institute of Technology, Pasadena, U.S.A. Additional information can be found on my full CV.

Selected publications

Clustering and Informative Path Planning for 3D Gas Distribution Mapping: Algorithms and Performance Evaluation

Ercolani C., Tang L., Humne A. A., and Martinoli A.
Published in IEEE Robotics and Automation Letters in 2022

A Distributed Source Term Estimation Algorithm for Multi-Robot Systems

Rahbar F. and Martinoli A.
Published in Proc. of the IEEE Int. Conf. on Robotics and Automation in 2020

Adaptive Risk-Based Replanning For Human-Aware Multi-Robot Task Allocation with Local Perception

Talebpour Z. and Martinoli A.
Published in Robotics and Automation Letters in 2019

Autonomous Feature Tracing and Adaptive Sampling in Real-World Underwater Environments

Quraishi A., Bahr A., Schill F., and Martinoli A.
Published in Proc. of the IEEE Int. Conf. on Robotics and Automation in 2018

Extending Urban Air Pollution Maps beyond the Coverage of a Mobile Sensor Network: Data Sources, Methods, and Performance Evaluation

Marjovi A., Arfire A., and Martinoli A.
Published in Proc. of the Int. Conf. on Embedded Wireless Systems and Networks in 2017

Vertex: A New Distributed Underwater Robotic Platform for Environmental Monitoring

Schill F., Bahr A., and Martinoli A.
Published in Proc. of the 13th Int. Symp. on Distributed Autonomous Robotic Systems in 2016

Mitigating Slow Dynamics of Low-Cost Chemical Sensors for Mobile Air Quality Monitoring Sensor Networks

Arfire A., Marjovi A., and Martinoli A.
Published in Proc. of the Int. Conf. on Embedded Wireless Systems and Networks in 2016

A Distributed Formation-Based Odor Source Localization Algorithm -Design, Implementation, and Wind Tunnel Evaluation

Soares J. M., Aguiar A. P., Pascoal A. M., and Martinoli A.
Published in Proc. of the 2015 IEEE Int. Conf. on Robotics and Automation in 2015

A Distributed Noise-Resistant Particle Swarm Optimization Algorithm for High-Dimensional Multi-Robot Learning

Di Mario E., Navarro I., and Martinoli A.
Published in Proc. of the 2015 IEEE Int. Conf. on Robotics and Automation in 2015

Accurate Indoor Localization with Ultra-Wideband using Spatial Models and Collaboration

Prorok A. and Martinoli A.
Published in International Journal of Robotics Research in 2014

A Fast On-Board Relative Positioning Module for Multi-Robot Systems

Pugh J., Raemy X., Favre C., Falconi R., and Martinoli A.
Published in IEEE Transaction on Mechatronic Systems in 2009

Multi-Robot Inspection of Industrial Machinery: From Distributed Coverage Algorithms to Experiments with Miniature Robotic Swarms

Correll N. and Martinoli A.
Published in IEEE Robotics and Automation Magazine in 2009

Social integration of robots in groups of cockroaches to control self-organized choices

Halloy J., Sempo G., Caprari G., Rivault C., Asadpour M., Tâche F., Saïd I., Durier V., Canonge S., Amé J.M., Detrain C., Correll N., Martinoli A., Mondada F., Siegwart R. R., and Deneubourg J. L.
Published in Science in 2007

Modeling of Swarm Robotic Systems: A Case Study in Collaborative Distributed Manipulation

Martinoli A., Easton K., and Agassounon W.
Published in International Journal of Robotics Research in 2004

Distributed Odor Source Localization

Hayes A. T., Martinoli A., and Goodman R. M.
Published in IEEE Sensors Journal in 2002

Infoscience

Teaching & PhD

PhD Students

Nicolaj Andreas Schmid, Yacine Derder, Lucas Cédric Wälti, Alexander Wallen Kiessling, Wanting Jin

Past EPFL PhD Students

Nicolaus Correll, James Pugh, Christopher Cianci, Thomas Lochmatter, Grégory Mermoud, Amanda Stella Markowska Prorok, Sven Adrian Gowal, José Nuno Ferreira Maia Pereira, William Christopher Evans, Ezequiel Leonardo Di Mario, Klara Maria Boberg, Adrian Arfire, Jorge Miguel Soares, Steven Adriaan Roelofsen, Milos Vasic, Bahar Haghighat, Zeynab Talebpour, Duarte Da Cruz Baptista Dias, Alicja Barbara Roelofsen, Anwar Ahmad Quraishi, Faezeh Rahbar, Cyrill Baumann, Chiara Ercolani, Izzet Kagan Erünsal

Past EPFL PhD Students as codirector

Pierre Roduit

Courses

Distributed intelligent systems

ENG-466

The goal of this course is to provide methods and tools for modeling distributed intelligent systems as well as designing and optimizing coordination strategies. The course is a well-balanced mixture of theory and practical activities.

Signals, instruments and systems

ENG-366

The goal of this course is to transmit knowledge in sensing, computing, communicating, and actuating for programmable field instruments and, more generally, embedded systems. The student will be able to put in practice the knowledge acquired using concrete software and hardware tools.