PhD Positions

Every year, the Dynamic Legged Systems lab (HyQ Project) has open PhD positions in the PhD Program Bioengineering and Robotics (curriculum: Advanced and Humanoid Robotics) of the Istituto Italiano di Tecnologia (IIT), an English language Institute. All the positions are fully funded.
An overview of all the PhD positions offered by IIT in collaboration with the University of Genova and an explaination of the application procedure can be found at the PhD school website: The list of open positions offered in the curriculum of Advanced and Humanoid Robotics (among which the DLS lab. positions can be found) is located at this webpage:
At the moment we have in our group the following open PhD position:

Hydraulic Quadruped Robots: Recovery Strategies for Dynamic Locomotion on Irregular Surfaces

Tutors: Michele Focchi, Victor Barasuol and Claudio Semini
Research Line: Dynamic Legged Systems lab, Dept. of Advanced Robotics (IIT)
To apply for this position, in the online application, choose the following course/theme:
Research theme 1: 6 Hydraulic Quadruped Robots: Recovery Strategies for Dynamic Locomotion on Irregular Surfaces
Description: The Hydraulic Quadruped robot -HyQ- is a fully torque-controlled hydraulically actuated quadruped robot, capable of locomotion over rough terrain and performing highly dynamic tasks such as jumping and running with a variety of gaits, e.g. [1,2]. It is a unique research platform, designed for unstructured environments, e.g. outdoors and disaster sites. These environments present several challenges to locomotion. Using a vision feedback,it is possible to plan appropriate motions that are taking into consideration the features of the terrain. Long term planning methods could deal with these terrains, but they reach their limits because they are inherently unable to cope with accumulation of errors. These errors can be due to tracking/filtering delays, inaccuracy of the 3D map, modeling errors, sensor calibration errors, unforeseen events (external pushes, slipping, rock falling) or simply by the fact that terrain can be changing (e.g. rolling stones). These errors would make the robot state drift away from the original plan. Recovery strategies (based on a map of the environment) can help to mitigate these errors [3,4].
This position will focus on the design of successful recovery strategies for stabilization to deal with a variety of terrain (e.g. climbing stairs, pile of rubble) in face of unpredicted situations (e.g. external pushes, stepping on rolling rocks or slippery surfaces).
Requirements: Background in robotics, computer science, electrical engineering or mechanical engineering. Mandatory: Basic knowledge on control and signal processing. Understanding of robot kinematics and dynamics, strong C++ skills. Creativity, problem-solving skills. Passionate for robotics and legged locomotion. Experience in Matlab. Desired but not mandatory: basic knowledge on neural networks and machine learning, 3D mapping, ROS and Python.
[1] V. Barasuol, J. Buchli, C. Semini, M. Frigerio, E. R. De Pieri, D. G. Caldwell, A Reactive Controller Framework for Quadrupedal Locomotion on Challenging Terrain. IEEE ICRA, 2013.
[2] M. Focchi, A. del Prete, I. Havoutis, R. Featherstone, D. G. Caldwell, C. Semini, High-slope terrain locomotion for torque-controlled quadruped robots. Autonomous Robots, 2017.
[3] V. Barasuol, M. Camurri, S. Bazeille, D. Caldwell, C. Semini, Reactive Trotting with Foot Placement Corrections through Visual Pattern Classification. IEEE/RSJ IROS, 2015.
[4] O. A. Villarreal, V. Barasuol, M. Camurri, L. Franceschi, M. Focchi, M. Pontil, D. G. Caldwell, C. Semini, Fast and Continuous Foothold Adaptation for Dynamic Locomotion Through CNNs. IEEE Robotics and Automation Letters, 2019.

Guidelines for the PhD application

In addition to the official online application, interested candidates should send their CV, a letter of motivation and the university transcripts to This email address is being protected from spambots. You need JavaScript enabled to view it., This email address is being protected from spambots. You need JavaScript enabled to view it. and to This email address is being protected from spambots. You need JavaScript enabled to view it., including the tag [PHD2019] in the email's subject line.

**Attention**: For a valid application, it is required that you fill the "Università Degli Studi Di Genova online application". All PhD courses at IIT are organized in collaboration with the University of Genoa. Information on the official PhD call and the full details and information on the application procedure are published here:, while the online application link is:


Please note that the online application procedure requires preparing and uploading a set of documents before the deadline. You first need to register online and then proceed to the online application.
It's strongly recommended to start the application process well before the deadline!

Bachelor and Master Students

The Dynamic Legged Systems lab is constantly looking for Bachelor and Master students who wish to perform an internship or their Bsc/Msc thesis in our labs. A list of currently available projects can be found below. To learn more about the project description, requirements and application procedure, click on the "Read More" button for each of the projects. For spontaneous applications, apart from the projects below, please send your CV to This email address is being protected from spambots. You need JavaScript enabled to view it.


Currently available projects

Locomotion Adaptation over Soft Terrain: Passivity & Stability Analysis

Legged locomotion over soft terrain is difficult due to the presence of unmodeled contact dynamics that locomotion controllers do not account for. This introduces uncertainty in locomotion and affects the stability and performance of the system.

To this end, we are currently looking for a highly motivated intern or master thesis student to work on the influence of soft terrain on the passivity and stability of WBCs for legged robots.

Read More

Implementation of a Decision Maker for Locomotion (internship)

The aim of this student project is to increase the level of autonomy of our locomotion framework. An effective locomotion framework encompasses different levels of autonomy. At a lower level we have several locomotion strategies (e.g. different gaits) that take care of keeping the stability while dealing with the terrain features but require high level commands (e.g. desired velocities from the user). On the other hand, at a higher level, the focus is on improving autonomy, by orchestrating the locomotion modules to fulfill higher level user requirements. These algorithms should take care of choosing the most suitable locomotion strategy and adapting the gait parameters (according to the terrain difficulty) in order to ensure task accomplishment (e.g. reach a goal, pick up an object).
Read More

State Estimation for Legged Robots (internship)

This project aims to further improve the implementation of state estimation algorithms for a range of diverse applications for quadruped robots. Some examples include probabilistic foot contact estimation and hetrogeneous sensor fusion for accurate state estimation. We are currently looking for a highly motivated, full-time internship position to work on the implementation, evaluation, and further development of state estimation algorithms into our legged robot framework.
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Contact Detection and Localization in Legged Robots (internship)

Our team is currently looking for a highly motivated student to conduct studies on algorithms for leg collision detection and localization. The accuracy of such information has direct impact on the locomotion performance and robustness, with strong impacts also on the algorithms responsable to estimate the robot world position and velocities. Therefore, precisely detecting where contacts happen is of high relevance for the robot navigation quality on natural and unstructed environments. In this project the student will have the opportunity to: do scientific development with state-ofthe-art algorithms; simulate proposed algorithms on the DLS software framework and experimentally test them on the real robot HyQ.
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Computer Vision for Legged Robots (internship)

Autonomous legged robots are required to handle a wide range of tasks in complex environments. Current computer vision algorithms are not robust in dynamic environments, however, using computer vision is critical to improving autonomy. It is well-known that video images provide rich information about the environment which is critical for localization in environments without a priori maps. The appointed candiate will work on the development and implementation of state-of-the-art computer vision algorithms
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