Memory of Motion (Memmo)

The project Memmo aims to solve the problem of generating complex movements for arbitrary robots with arms and legs interacting in a dynamic environment by 1) relying on massive off-line caching of pre-computed optimal motions that are 2) recovered and adapted online to new situations with real-time tractable model predictive control and where 3) all available sensor modalities are exploited for feedback control going beyond the mere state of the robot for more robust behaviors.

Compliant Feedback Control of Legged Robots

The goal of this project is to achieve reliable locomotion behaviors in semi-structured environments with the humanoid robots HRP-2 and Pyrene. This project relies on model-based feedback control techniques, such as inverse-dynamics and model predictive control.

Robust Robotics

Nowadays legged robots are capable of performing locomotion and manipulation in semi-structured environments, but with a low level of reliability, which makes their application in disaster-recovery scenarios difficult, if not impossible. However, if we look at the results that researchers in robotics and animation have achieved in simulation, we can see that simulated robots/avatars can easily and reliably perform dynamic movements such as walking, running, jumping, kicking. What is preventing real robots from showing similar performance?

Recent Publications

More Publications


Balancing Legged Robots on Visco-Elastic Contacts - Workshop @ RSS 2019, Freiburg, Germany

The rise of the robots - GIZ tech2D, Technology Forum for Sustainable Development 2018, Frankfurt, Germany

Addressing Constraint Robustness to Torque Errors in Task-Space Inverse Dynamics - RSS 2015, Rome, Italy


Optimization-Based Robot Control

Industrial Engineering Department, July 2019, University of Trento (Trento, Italy)

A 12-hour course for PhD students about reactive control (TSID) and trajectory optimization for humanoid robots. Here you can find the videos of all the lectures (except the first one, which wasn’t recorded). Here you can find the slides:

Task-Space Inverse Dynamics (TSID)

Memmo Winter School, January 28-31 2019, IDIAP (Martigny, Switzerland)

A 3-hour class about TSID, covering both theory and implementation. Here you can find videos and slides:

I have also given a class on robust TSID:


“Second Workshop on Perception and Planning for Legged Robot Locomotion in Challenging Domains”

Organizers: D. Kanoulas, I. Havoutis, M. Fallon, A. Del Prete, E. Yoshida.

Full-day workshop at ICRA 2017, Singapore.

“Robust Optimization-Based Control and Planning for Legged Robots”

Co-organized with Russ Tedrake, (MIT, USA) and Alexander Herzog (Max Planck IS, Germany).

Full-day workshop at ICRA 2016, Stockholm (Sweden).

“Torque-Controlled Humanoids”

Co-organized with Luis Sentis (University of Texas, Austin).

Full-day workshop at Humanoids 2013, Atlanta (Georgia, USA).