Organisation/Company: CNRS
Department: Institut de recherche en informatique et systèmes aléatoires
Research Field: Engineering, Computer Science, Mathematics
Researcher Profile: First Stage Researcher (R1)
Country: France
Application Deadline: 25 Nov 2024 - 23:59 (UTC)
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 35
Offer Starting Date: 3 Feb 2025
Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
Is the Job related to staff position within a Research Infrastructure? No
Offer Description The PhD will be carried out in the Rainbow team at IRISA/Inria, Rennes.
- The Ph.D. position is full-time for 3 years (standard duration in France). The position will be paid according to the French salary regulations for PhD students.
- We do high quality and impactful research in robotics, publishing on the major journals and conferences.
- We often collaborate with other top researchers in Europe and worldwide.
- You will have access to a well-established laboratory including: two flying arenas equipped with motion tracking systems, several quadrotors, and a few fully-actuated manipulators; one robotic manipulation lab equipped with several robotic arms, like the Franka Emika Panda.
- You will be part of an international and friendly team. We organize several events, from after works to multi-day lab retreats.
- Regular visits and talks by internationally known researchers from top research labs.
Expected Competences - M.Sc. degree in mechatronics, robotics, engineering, computer science (or related fields)
- Excellent written and spoken English skills
- Good experience in C/C++, ROS, Matlab/Simulink, CAD
- Good experience with numerical trajectory optimization tools for robotics (e.g., use of CaSaDi, Acado, Autodiff, Crocoddyl, etc.)
- Scientific curiosity, large autonomy, and ability to work independently
- Experience with robotic systems and/or aerial robots is a plus
PhD Topic Over the past decade, there has been a surge in the exploration of aerial robots able to perform challenging physical interaction tasks. However, the inherent limitations in the payload capacity of individual drones have prompted researchers to explore the potential of collaborative efforts among teams of aerial robots. This collaborative approach is envisioned to revolutionize various application domains, including construction, inspection, maintenance, and beyond. One of the preferred solutions to enable the aerial manipulation/transportation of objects is using cables or tethers to suspend loads to the robots. This solution is lightweight and decouples the attitude dynamics of the aerial robots from that of the load, which in turn increases the stability of the system.
Research Objectives The primary objective of this Ph.D. thesis is to explore sensor-based and distributed coordination strategies for multi-aerial robot systems with cable-suspended loads, facilitating collaborative object manipulation and transportation through local interactions. Distributed solutions pose particular challenges, especially when addressing communication constraints among the robots. The objective is then to consider hierarchical strategies where robots communicate at a low frequency and coordinate at a higher/planning level, subsequently executing the plan through local implicit communication based on sensor-based feedback such as vision and/or force sensing.
Envisaged Activities Envisioned solutions will build upon existing centralized or kinematic results and communication-less regulation approaches to propose a fully sensor-based, dynamics-based, and distributed framework for collaborative agile manipulation of cable-suspended loads. For the control side, a starting point are the existing centralized approaches based on Model Predictive Control (MPC) for single- and multi-aerial robots. Our team has undertaken preliminary work exploring the extension of these approaches through a distributed MPC solution, initially at a kinematic level. Should this endeavor yield promising results, a potential trajectory involves advancing the algorithm to operate at a dynamic level. For the sensing side, the starting point will be the works on sensor-based collaborative global state estimation for multi-robot systems.
Experimental Validation The devised coordination strategies for the manipulation and transportation of cable-suspended loads will undergo thorough validation and testing using the cable-driven platform, already present at Rainbow.
Related References [1] S. Sun and A. Franchi, "Nonlinear MPC for Full-Pose Manipulation of a Cable-Suspended Load using Multiple UAVs," 2023 International Conference on Unmanned Aircraft Systems (ICUAS), Warsaw, Poland, 2023, pp. 969-975.
[2] Sanalitro, D. (2022). Aerial Cooperative Manipulation: full pose manipulation in air and in interaction with the environment (Doctoral dissertation, INSA de Toulouse).
[3] D. Sanalitro, H. Savino, M. Tognon, J. Cortés, and A. Franchi "Full-pose manipulation control of a cable-suspended load with multiple UAVs under uncertainties". IEEE Robotics and Automation Letters, 2020, 5(2), 2185-2191.
[4] C. Gabellieri, M. Tognon, D. Sanalitro and A. Franchi, "Force-Based Pose Regulation of a Cable-Suspended Load Using UAVs with Force Bias," 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, MI, USA, 2023, pp. 6920-6926.
[5] N. de Carli, P. Salaris, P. Robuffo Giordano. Multi-Robot Active Sensing for Bearing Formations. MSR 2023 - IEEE International Symposium on Multi-Robot & Multi-Agent Systems, Dec 2023, Boston (MA), United States. pp.1-7.
[6] L. Guanrui, and G. Loianno. "Nonlinear Model Predictive Control for Cooperative Transportation and Manipulation of Cable Suspended Payloads with Multiple Quadrotors." arXiv preprint arXiv:2303.06165 (2023).
[7] A. Ollero, M. Tognon, A. Suarez, D. J. Lee, and A. Franchi. "Past, present, and future of aerial robotic manipulators." IEEE Trans. on Robotics, 2021.
[8] S., Ola, and M. Schwager. "Distributed Model Predictive Control via Separable Optimization in Multi-Agent Networks." IEEE Transactions on Automatic Control (2023).
[9] L. Peric, Brunner, M., Bodie, K., M. Tognon, and Siegwart, R., "Direct Force and Pose NMPC with Multiple Interaction Modes for Aerial Push-and-Slide Operations", in 2021 IEEE Int. Conf. on Robotics and Automation, Xi'an, China, 2021.
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