Open Research Internship position in
Cooperative multi-robot non-prehensile manipulation
Short abstract: The goal of this Master Thesis is to propose novel distributed control algorithms for the non-prehensile manipulation of unknown objects with a group of mobile robots.
Team: Rainbow IRISA/Inria Rennes, France
Advised by: Paolo Robuffo Giordano, and Esteban Restrepo
Contact: prg@irisa.fr – esteban.restrepo@irisa.fr
How to apply: Interested candidates are requested to apply via this form.
Description: How can a team of robots work together to push and transport unknown objects without prior knowledge of their properties? This Master’s thesis aims to develop innovative distributed control algorithms that enable a group of mobile robots to autonomously manipulate objects of unknown properties (mass, friction, and center of mass), overcoming sensing and actuation constraints through intelligent collaboration.
Background and Motivations: Most of the current works addressing the problem of clustering for multi-agent systems are concerned with generic unconstrained agents, thus neglecting the constraints and specificity of networks of mobile robots in terms of limited sensing capabilities. Moreover, they only study the conditions for convergence of the agents to small groups, i.e. cluster consensus, rather than the autonomous formation of clusters. There are few works addressing the autonomous achievement of clusters in a network of mobile robots based on distributed and local interactions among the robots, none of which take also into account the sensing constraints inherent to these types of systems.
General Objectives: The goal of this Master Thesis is to develop novel distributed control algorithms that allow a team of mobile robots to push and manipulate objects without prior knowledge of their properties. Moreover, the team of robots should be able to adapt and reconfigure dynamically when dealing with different objects, taking into account constraints such as limited sensing range, field of view, and actuation capabilities. The proposed algorithms will be validated through simulations and real-world experiments using a team of mobile robots.
This thesis will provide exciting opportunities to explore cutting-edge control methodologies for multi-robot collaboration.
Envisaged Activities
1. Literature review of the related works and familiarize with the experimental setup in the team
2. Take over the existing works and work on the design and analysis of a control algorithm for autonomous pushing of unknown objects with multi-robot systems
3. Implement and validate in simulation the proposed algorithms
4. Validate experimentally the scenario on a team of mobile robots
Skills/Requirements
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High motivation and interest in the topic
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Good knowledge in control theory and robot modeling
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Good experience using Matlab/Simulink
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Basic knowledge of control and analysis of multi-agent systems is appreciated
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Previous experience with Python/C++ and ROS2 is appreciated
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Scientific curiosity
Conditions
The work will be carried in English at the Centre Inria de l’Université de Rennes research center in Rennes, France.
Financial support offered to the student: gratification de 4,35 € / h
How to apply
Interested candidates are requested to apply via this form.
The position will remain open until a satisfactory candidate is found. In case of positive feedback, you will be contacted. If not positive, you won’t hear back.
Supervisor(s): Dr. Esteban Restrepo and Dr. Paolo Robuffo Giordano
References
• Rosenfelder, M., Ebel, H., & Eberhard, P. (2022, August). A force-based control approach for the non-prehensile cooperative transportation of objects using omnidirectional mobile robots. In 2022 IEEE Conference on Control Technology and Applications (CCTA) (pp. 349-356). IEEE.
• Bertoncelli, F., & Sabattini, L. (2021, December). Planar Pushing Manipulation with a Group of Mobile Robots. In 2021 20th International Conference on Advanced Robotics (ICAR) (pp. 897-904). IEEE.
• Tang, Z., Feng, Y., & Guo, M. (2024). Collaborative Planar Pushing of Polytopic Objects with Multiple Robots in Complex Scenes. arXiv preprint arXiv:2405.07908.
• Robuffo Giordano, P., Franchi, A., Secchi, C., & Bülthoff, H. H. (2013). A passivity-based decentralized strategy for generalized connectivity maintenance. The International Journal of Robotics Research, 32(3), 299-323.
• Bertoncelli, F., Selvaggio, M., Ruggiero, F., & Sabattini, L. (2022, October). Task-oriented contact optimization for pushing manipulation with mobile robots. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 1639-1646). IEEE.
