Marco Pavone

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Assistant Professor
Stanford University
Department of Aeronautics and Astronautics

Director, Autonomous Systems Laboratory
Assistant Professor (by courtesy), Department of Electrical Engineering
Assistant Professor (by courtesy), Institute for Computational and Mathematical Engineering
Assistant Professor (by courtesy), Information Systems Laboratory

Ph.D. Massachusetts Institute of Technology, 2010

Email: [last name]@stanford.edu

Phone: (650) 723 4432

Dr. Marco Pavone is an Assistant Professor of Aeronautics and Astronautics at Stanford University, where he also holds courtesy appointments in the Department of Electrical Engineering, in the Institute for Computational and Mathematical Engineering, and in the Information Systems Laboratory. He is a Research Affiliate at the NASA Jet Propulsion Laboratory (JPL), California Institute of Technology. Before joining Stanford, he was a Research Technologist within the Robotics Section at JPL. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. Dr. Pavone’s areas of expertise lie in the fields of controls and robotics.

Dr. Pavone is a recipient of a NASA Early Career Faculty award, a Hellman Faculty Scholar Award, and was named NASA NIAC Fellow in 2011. At JPL, Dr. Pavone worked on the end-to-end optimization of the mission architecture for the Mars sample return mission. He has designed control algorithms for formation flying that have been successfully tested on board the International Space Station.

Dr. Pavone is the Director of the Autonomous Systems Laboratory (ASL). The goal of ASL is the development of methodologies for the analysis, design, and control of autonomous systems, with a particular emphasis on large-scale robotic networks and autonomous aerospace vehicles. The lab combines expertise from control theory, robotics, optimization, and operations research to develop the theoretical foundations for networked autonomous systems operating in uncertain, rapidly-changing, and potentially adversarial environments. Theoretical insights are then used to devise practical, computationally-efficient, and provably-correct algorithms for field deployment. Applications include robotic transportation networks, sensor networks, agile control of spacecraft during proximity operations, and mobility platforms for extreme planetary environments. Collaborations with NASA centers are a key component of the research portfolio.

Specifically, ASL's current research is along four main dimensions:

  • Cooperative control of robotic networks with application to future urban transportation systems and formation flying (see videos of some tests in space).

  • Motion planning in dynamic and uncertain environments with application to spacecraft proximity operations (see project description)

  • Unconventional space robotics (see project description)

  • Risk-sensitive and risk-constrained stochastic optimal control

The publications of the ASL lab are available here.

News

  • June, 8, 2014: Our paper about rapid multi-robot deployment will appear in the ASME Journal of Dynamic Systems, Measurement and Control.

  • May, 28, 2014: Two working papers about kinodynamic motion planning: the driftless case is here while the drift case is here.

  • May, 27, 2014: Our paper about queuing theoretical models for mobility-on-demand systems has been nominated for best paper award at the RSS conference.

  • May, 17, 2014: Our two papers about computation of reachability sets via machine learning and time-constrained robot deployment will appear at IROS.

  • April, 23, 2014: We are organizing a special issue of the Autonomous Robots journal on the topic of constrained decision making in robotics. Details will be posted soon.

  • April, 17, 2014: Forbes features our work about robotaxis.

  • April, 14, 2014: Our paper about queuing theoretical models for mobility-on-demand systems will appear at RSS.

  • April, 11, 2014: We submitted to IJRR a paper about FMT*, a novel sampling-based algorithm for (asymptotically-) optimal robotic motion planning.

  • April, 2, 2014: Our proposal about low-gravity mobility platforms has been selected by NASA for flight on a parabolic aircraft.

  • April, 1, 2014: We are organizing a workshop at RSS about “Constrained decision-making in robotics: models, algorithms, and applications”.

  • March, 20, 2014: We submitted a paper about fundamental limitations of performance in robotic networks to CDC.

Contact

Stanford University, Department of Aeronautics & Astronautics

William F. Durand Building, Rm. 261

496 Lomita Mall

Stanford, CA 94305-4035