Searching for a motivated candidate for PhD position in collaborative robotics at UTTOP, Univ. of Toulouse, France.

Bellow the information about the PhD and the application (deadline March 30th )

Title:Online mobile human–robot co-manipulation using multi-view perception and joint control

Period: October 2026 – September 2029

Contacts: Wiem BELHEDI (wiem.belhedi@uttop.fr), Mourad BENOUSSAAD (mourad.benoussaad@uttop.fr)

Keywords: Mobile Collaborative robots, joint control, perception

Scientific context and objectives:

Collaborative robotics is experiencing significant growth across numerous domains, particularly in dynamic industrial environments where robots are required to share the workspace and sometimes the task with human operators. In this context, physical human-robot interaction (pHRI) constitutes a major research field, aiming to enable safe, intuitive, and efficient exchange of forces between a human and a robot.

Among the most advanced forms of pHRI, human-robot co-manipulation consists of jointly manipulating an object or tool in a continuous manner, combining the human’s cognitive and perceptual capabilities with the robot’s precision and strength.

However, most existing work is limited to manipulators mounted on fixed bases, whereas many industrial and logistics tasks require mobility, repositioning capabilities, and greater spatial adaptability.

This motivates the study of mobile manipulator robots, which combine a mobile base and a robotic arm, in the context of human–robot collaboration. These systems offer increased flexibility in terms of use, but introduce new complexities related to base-arm coordination, onboard perception, and the stability of physical interaction. It is within this context that this PhD research is situated.

The PhD project aims to address three major scientific challenges:

• The dynamic coordination between the robotic arm and the mobile base during continuous physical interaction, by integrating human-applied forces as informative inputs for the overall system control.

• Task-oriented multi-sensor, multi-view perception, combining data from LiDAR sensors, RGB-D cameras, and force sensors, in order to ensure consistency between navigation, manipulation, and interaction.

• Human-robot authority sharing, through an adaptive shared control framework incorporating intention estimation and continuous adaptation of compliance parameters.

The developments will be experimentally validated on a real robotic platform composed of a Clearpath Ridgeback mobile base and a KUKA iiwa collaborative arm, in a representative scenario involving the co-transport and positioning of an object.

The PhD will contribute to proposing an integrated architecture combining perception, joint control, and quantitative evaluation of collaborative performance, with the objective of improving the fluency, safety, and efficiency of collaborative mobile manipulation systems.

Candidate skills:

The candidate should have a Master’s degree (Master 2 or equivalent) with research experience, as well as a strong background in robotics (mobile robotics, manipulators, and cobots). A strong interest in experimentation on real robotic systems is essential, and hands-on experience in this area would be a major asset.

Knowledge in artificial intelligence and computer vision is also highly appreciated. The candidate must also have strong programming skills (Python, C++) and experience with ROS / MC_RTC (preferred).

About MAVRICS

The PhD is a part of the activities of the MAVRICS team, specialized in collaborative robotics, human–robot interaction, and adaptive control. (https://www.lgp.enit.fr/fr/composition-des-equipes-2/departement-scient…).

Instruction to apply:

Please send your CV, motivation letter mentioning at least two referees, who can be contacted if necessary, to:

Wiem BELHEDI (Wiem.belhedi@uttop.fr) and Mourad BENOUSSAAD (mourad.benoussaad@uttop.fr).

Deadline to apply: March 30th, 2026

Applications submitted before the deadline may be processed as quickly as possible.

Refrences :

[1] M. Mujica; M. Benoussaad; J.-Y. Fourquet : Evaluation of human–robot object co-manipulation under robot impedance control. Proc. IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 9143–9149, 2020.

[2] D. Watkins-Valls; P. K. Allen; H. Maia; M. Seshadri; J. Sanabria; N. Waytowich; J. Varley : Mobile manipulation leveraging multiple views. In Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4585–4592, IEEE, 2022.

[3] M. Mujica; M. Crespo; M. Benoussaad; S. Junco; J.-Y. Fourquet : Robust variable admittance control for human–robot co-manipulation of objects with unknown load. Robotics and Computer-Integrated Manufacturing, vol. 79, 102408, 2023.