Andrea Del Prete

Andrea Del Prete

Professor of Robotics

University of Trento

Biography

Since 2022 I have been an associate professor in the Industrial Engineering Department of the University of Trento (Italy), where I am teaching optimal control and reinforcement learning for robotics, and computer programming in C++. From 2019 to 2021 I had been a tenure-track assistant professor (RTD-B) in the same department.

In 2018 I had been a research scientist in the Movement Generation and Control group at the Max-Planck Institute for Intelligent Systems (Tübingen, Germany), under the lead of Ludovic Righetti.

From 2014 to 2017 I had been an associated researcher in the Gepetto team (LAAS-CNRS, Toulouse), where I have been working with the humanoid robot HRP-2. My main collaborations were with Nicolas Mansard, Olivier Stasse, Steve Tonneau and Justin Carpentier.

Before going to LAAS I had spent four years (3 of PhD + 1 of post-doc) at the Italian Institute of Technology (IIT, Genova, Italy), where I had been working with Lorenzo Natale and Francesco Nori on the iCub humanoid robot.

In 2013 I also started a fruitful collaboration with Michele Focchi, an IIT researcher working with the Hydraulic Quadruped HyQ.

Since 2020 I am serving as an Associate Editor for IEEE Robotics and Automation Letters.

Interests
  • Robot Control
  • Reinforcement Learning
  • Trajectory Optimization
  • Safety Certificates
  • Numerical Algorithms
Education
  • PhD in Robotics, 2013

    Italian Institute of Technology

  • MEng in Computer Engineering, 2009

    University of Bologna

  • BSc in Computer Engineering, 2006

    University of Bologna

Experience

 
 
 
 
 
PhD
January 2010 – December 2012 Genova, Italy
Motion and force control of the iCub humanoid robot, using force and tactile sensors.
 
 
 
 
 
Post-Doc
January 2013 – December 2013 Genova, Italy
Multi-contact force control for the iCub humanoid robot, in the framework of the CoDyCo EU project.
 
 
 
 
 
Post-Doc / Associated Researcher
January 2014 – December 2017 Toulouse, France
Control of the humanoid robot HRP-2 using robust optimization, stochastic optimization, motor identification, torque control, hierarchical trajectory optimization.
 
 
 
 
 
Research Scientist
January 2018 – December 2018 Tuebingen, Germany
Optimization-based control for the humanoid robot Athena.
 
 
 
 
 
Assistant Professor (tenure track)
January 2019 – December 2021 Trento, Italy
Research on robot co-design, robust and stochastic model predictive control. Teaching computer programming and optimization-based robot control.
 
 
 
 
 
Associate Professor
January 2022 – Present Trento, Italy
Carrying out research on merging learning and model-based techniques to achieve safe robot control. Teaching courses on robotics and programming for bachelor and master students.

Courses

Control of Legged Robots
A 12-hour course for PhD students about reactive control (TSID) and trajectory optimization for legged robots.
Control of Legged Robots
Optimization and Learning for Robot Control
A 48-hour course for master students focusing on modern optimal control and reinforcement learning techniques for robot control
Optimization and Learning for Robot Control
Task-Space Inverse Dynamics
A 3-hour course for PhD students about Quadratic-Progamming-based dynamic control.
Task-Space Inverse Dynamics

Recent Publications

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(2024). CACTO-SL: Using Sobolev Learning to improve Continuous Actor-Critic with Trajectory Optimization. Learning for Dynamics and Control Conference (under review).

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(2024). Co-designing versatile quadruped robots for dynamic and energy-efficient motions. IEEE Transaction on Robotics (under review).

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(2024). GIBO: Global Integral-Based Optimization. Learning for Dynamics and Control Conference (under review).

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(2024). Receding-Constraint Model Predictive Control using a Learned Approximate Control-Invariant Set. IEEE International Conference on Robotics and Automation.

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(2023). CACTO: Continuous Actor-Critic With Trajectory Optimization - Towards Global Optimality. IEEE Robotics and Automation Letters.

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