See below for how to apply
Motivations and general objectives
The deployment of fleets of robotic vehicles has been shown to be effective for a wide range of applications based on cooperative tasks such as reconnaissance, surveillance, load transportation and imaging. While a fixed number of cooperative robotic agents may be capable of performing “simple” short-term tasks such as, e.g., formation tracking, flocking, or area coverage, it may prove limiting in many practical scenarios. Indeed, as the field advances, applications of multi-robot systems are starting to shift from such relatively simple tasks, to more complex long-term and persistent missions that require the robots to be deployed for longer periods of time, usually surpassing the battery-charge duration of the devices, forcing individual robots to leave the network for recharging and (possibly) returning when fully charged. Moreover, as tasks get more complex and are designed for dynamic and, often, antagonistic environments, failure of individual robots due to malfunctioning or attacks cannot always be prevented. Equivalently, when addressing tasks in uncertain or unknown environments, in order to successfully accomplish the mission, new robots may be required to join the system dynamically as the task specification or the environment evolve. Usually during the development of a mission both the addition and removal of agents are bound to happen, oftentimes, simultaneously.
From a control-systems theory point of view, we refer to the system of multiple cooperative robots where agents can be added or removed as an Open Multi-Robot System (OMRS). Considering the OMRS as a single system of systems means that the dimension of the state of the system increases or decreases, respectively, as agents are added or removed. Therefore, OMRS are modeled as impulsive multi-dimensional switched systems. Recently, in our team we have started considering the coordination of OMRS in an energy-aware framework based on the concepts of impulsive switched systems, passivity, and energy-tanks. In this framework, each agent possesses a virtual energy reservoir that is filled or depleted distributedly in order to account for the energy jumps of the OMRS, due to the addition/removal of agents, in a passive way. Based on the energy tanks a distributed energy-based switching condition is established for the OMRS so that it can handle the addition and removal of agents (or groups thereof) autonomously while preserving the passivity of the system.
The goal of this Master Thesis is to keep working on the topic of energy-aware coordination of open multi-robot systems by building on top of the work done so far in the team. We are interested in several possible extensions:
Implementation of the energy-tanks-based coordination framework in a long-term mission simulation scenario and experimental validation on the fleet of quadrotor UAVs of the team.
Possibility to extend the framework by considering negative interconnections between the agents in order to model antagonistic and non-cooperative interactions such as, e.g., obstacle avoidance, group splitting, or attacks.
Proposed work plan
At first, the student will become familiar with the relevant literature on this subject (some references are listed below), and with the quadrotor UAVs and the software used in the team for simulations and experimental implementation (ROS, OLIVE, Matlab).
Then, the student will take over the existing code for multi-robot coordination and adapt it to the energy-aware OMRS framework and a specific mission scenario to be tested on simulation.
Subsequently, the student will be able to start one of the activities listed above: (A) running experiments on our fleet of drones, and (B) considering antagonistic and non-cooperative interactions modeled by negative interconnections.
Desired profile and skills
The successful applicant should have good knowledge of mobile robotics and UAV modeling and control (particularly of a quadrotor). She/he should have good knowledge of computer programming (C/C++ or Python, MATLAB). Basic knowledge of multi-agent systems modeling and control would be appreciated; advance knowledge of such themes is welcome but not required.
Six months research internship. The work will be carried in English at the Inria Rennes Bretagne Atlantique research center.
Financial support offered to the student: gratification de 4.05 € / h
How to apply
Candidates should provide a cover letter, a detailed CV, available grades from the current and previous years, the contact information of 1 or 2 referees, and the desired start and finish dates for the internship to:
J. Cortés, M. Egerstedt. Coordinated Control of Multi-Robot Systems: A Survey. SICE Journal of Control, Measurement, and System Integration, vol. 10, no. 6, pp. 495-503, 2017.
P. Robuffo Giordano, A. Franchi, C. Secchi, H. H. Bülthoff. A passivity-based decentralized strategy for generalized connectivity maintenance. The International Journal of Robotics Research, vol. 32, no. 3, pp. 299-323, 2013.
F. Califano, R. Rashad, C. Secchi, S. Stramigioli. On the Use of Energy Tanks for Robotic Systems. In: Borja, P., Della Santina, C., Peternel, L., Torta, E. (eds) Human-Friendly Robotics 2022. Springer Proceedings in Advanced Robotics, vol 26, pp. 174-188, 2022.
M. Xue, Y. Tang, W. Ren, F. Qian. Stability of multi-dimensional switched systems with an application to open multi-agent systems. Automatica, vol. 146, 110644, 2022.
P. Şekercioğlu, I. Sarras, A. Loría, E. Panteley, J. Marzat. Bipartite Formation over Undirected Signed Networks with Collision Avoidance. 2023. ⟨hal-04049669⟩