@article {2019k-FurNaiZacFra,
	title = {Input Allocation for the Propeller-Based Overactuated Platform ROSPO},
	journal = {IEEE Trans. on Control Systems Technology},
	volume = {18},
	year = {2019},
	month = {11/2020},
	pages = {2720-2727},
	abstract = {We apply input allocation to a redundantly actu- ated platform driven by tilting aerodynamic propulsion units: the ROtor graSPing Omnidirectional (ROSPO). This platform represents a novel testbed for redundancy allocation designs in propeller driven platforms. The control solution is based on a hierarchical architecture, made of a high level controller for trajectory tracking, and a nonlinear input allocation algorithm. The algorithm exploits the input redundancy to take into account soft constraints associated to physical saturation limits of the actuators, and also induce reduced energy consumption. The actuator dynamics is fully taken into account in the framework and a rigorous proof of asymptotic tracking of time-varying references is guaranteed despite the impossibility of an instanta- neous force execution. The experiments on the ROSPO platform clearly show the practicability and effectiveness of the proposed approach, as well as its scalability with different degrees of over- actuation levels.},
	doi = {10.1109/TCST.2019.2944341},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2019k-FurNaiZacFra.pdf},
	author = {Michele Furci and Carlo Nainer and Luca Zaccarian and Antonio Franchi}
}
@conference {2018o-FurBicFra,
	title = {Design and Input Allocation for Robots with Saturated Inputs via Genetic Algorithms},
	booktitle = {12th IFAC Symposium on Robot Control},
	year = {2018},
	month = {08/2018},
	address = {Budapest, Hungary},
	abstract = {In this paper we consider fully-actuated and redundantly-actuated robots, whose saturated inputs can have high bandwidth or can be slowly varying (with dynamics). The slowly varying inputs can be considered as configurations for the system. The proposed strategy allows to find the optimal actuators{\textquoteright} configuration to optimize a cost function as the manipulability or the energy consumption. The approach allows for both a static design, which can include actuators{\textquoteright} parameters such as position, orientation, saturations, numbers of actuators, and for a dynamic design, where the configurations can be controlled by an input of the system. A generalized solution to the optimal problem is proposed with the use of genetic algorithms. The results are validated in two simulation scenarios: a reconfiguration of the actuators orientation of an redundantly-actuated planar robot for trajectory tracking and the design optimization of the orientation of the motors in a generalized hexa-rotor with arbitrary propeller orientation.},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2018o-FurBicFra-preprint.pdf},
	author = {Michele Furci and Davide Bicego and Antonio Franchi}
}
@conference {2017j-NaiFurSeuZacFra,
	title = {Hierarchical Control of the Over-Actuated ROSPO Platform via Static Input Allocation},
	booktitle = {20th IFAC World Congress},
	year = {2017},
	month = {07/2017},
	address = {Toulouse, France},
	abstract = {This paper addresses the problem of control allocation applied to an over-actuated hovercraft-type vehicle. A hierarchical control architecture, consisting of a high level controller for trajectory tracking, and a control allocation algorithm, is developed and proved to be effective in tracking a desired trajectory while optimizing some cost related to actuator constraints. The control allocation algorithm exploits the redundancy of the system in order to keep the actuator states inside their saturation limits and tries to minimize the power consumption of the propellers. Unlike other papers on control allocation, actuator dynamics is taken into account. The control architecture is tested through simulations that well illustrate the capabilities of the proposed control design},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2017j-NaiFurSeuZacFra-preprint.pdf},
	author = {Carlo Nainer and Michele Furci and Alexandre Seuret and Luca Zaccarian and Antonio Franchi}
}
@conference {2017m-SolFurCorFra,
	title = {Multi-Robot Path Planning with Maintenance of Generalized Connectivity},
	booktitle = {The 1st Int. Symp. on Multi-Robot and Multi-Agent Systems},
	year = {2017},
	month = {12/2017},
	address = {Los Angeles, CA},
	abstract = { This paper addresses the problem of generating a path for a fleet of robots navigating in a cluttered environment, while maintaining the so called generalized connectivity. The main challenge in the management of a group of robots is to ensure the coordination between them, taking into account limitations in communication range and sensors, possible obstacles, inter-robot avoidance and other constraints. The Generalized Connectivity Maintenance (GCM) theory already provides a way to represent and consider the aforementioned constraints, but previous works only find solutions via locally-steering functions that do not provide global and optimal solutions. In this work, we merge the GCM theory with randomized path- planning approaches, and local path optimization techniques to derive a tool that can provide global, good-quality paths. The proposed approach has been intensively tested and verified by mean of numerical simulations.},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2017m-SolFurCorFra-preprint.pdf},
	author = {Yoann Solana and Michele Furci and Juan Cort{\'e}s and Antonio Franchi}
}
