PhD Position F/M Inexact optimization for the control of robots

June 15, 2023
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2023-06327 - PhD Position F/M Inexact optimization for the control of robots

Contract type : Fixed-term contract

Level of qualifications required : Graduate degree or equivalent

Fonction : PhD Position


In the current time of major, global ecological crisis, robots could help us satisfy more efficiently our most basic needs (food, health, clothing, housing, transport), but to do so, they should reduce their own ecological footprint, considering the energy and overall resources necessary to manufacture and operate them. One overlooked aspect in this regard is the design and implementation of control laws, which can lead to intensive computations and impact the whole hardware design of robots.

The control of complex robots is commonly computed by numerically solving optimization problems 1,2. These problems are often small enough (from tens to a few thousand variables) that they can be solved exactly, or with the highest numerical precision available. It would be beneficial, however, to study what precision is really needed at the different computation steps: formulation of the problem, accuracy of the solution or inner computations of the optimization. This could help perform cheaper computations, allowing faster resolution and better energy efficiency.

The goal of this PhD is to develop numerical formulations and dedicated solvers taking advantage of a reduced need for precision, to decrease the computations footprint. In particular, classical decisions made within optimization algorithms will be revisited with the inexact aspect in mind, to apply to cases where the input and output precisions are orders of magnitude lower than usually considered in optimization theory. The developments will be applied to the control of different robots in various scenarios (humanoid, quadruped and industrial manipulator robots as well as self-driving vehicles).

Machine learning approaches have been providing very interesting solutions to various robotics problems recently, but these solutions are approximate by construction. This connection between optimization and machine learning through the role of approximate solutions appears to be a key question to investigate more advanced control of robots.

References 1 J. Carpentier, P.-B. Wieber, “Recent progress in legged robots locomotion control”, Current Robotics Reports, vol. 2(3), 2021 2 P. Wensing, M. Posa, Y. Hu, A. Escande, N. Mansard, A. Del Prete “Optimization-Based Control for Dynamic Legged Robots”, submitted to IEEE Transactions on Robotics, 2022 3 N.A. Villa, J. Englsberger, P.-B. Wieber "Sensitivity of legged balance control to uncertainties and sampling period", IEEE Robotics and Automation Letters, 2019 4 A. Bambade, S. El-Kazdadi, A. Taylor, and J. Carpentier "PROX-QP: Yet another Quadratic Programming Solver for Robotics and beyond", Robotics: Science and Systems 2022


Technical skills and level required :

  • A strong background in robotics and numerical optimization. Machine learning is a plus.
  • A good knowledge of C++ and Python
  • Languages :

  • Fluent communication in French or English
  • Ability to read and write technical documents in English
  • Relational skills :

  • Ability to work in a team
  • Benefits package
  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage
  • General Information
  • Theme/Domain : Robotics and Smart environments
  • Town/city : Paris
  • Inria Center : Centre Inria de Paris
  • Starting date : 2023-10-01
  • Duration of contract : 3 years
  • Deadline to apply : 2023-06-15
  • Contacts
  • Inria Team : WILLOW
  • PhD Supervisor : Escande Adrien / [email protected]
  • About Inria

    Inria is the French national research institute dedicated to digital science and technology. It employs 2,600 people. Its 200 agile project teams, generally run jointly with academic partners, include more than 3,500 scientists and engineers working to meet the challenges of digital technology, often at the interface with other disciplines. The Institute also employs numerous talents in over forty different professions. 900 research support staff contribute to the preparation and development of scientific and entrepreneurial projects that have a worldwide impact.

    Instruction to apply

    Defence Security : This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment.

    Recruitment Policy : As part of its diversity policy, all Inria positions are accessible to people with disabilities.

    Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed.

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