@conference {2020h-PetSanTogMilCorFra,
	title = {Inertial Estimation and Energy-Efficient Control of a Cable-suspended Load with a Team of UAVs},
	booktitle = {2020 Int. Conf. on Unmanned Aircraft Systems},
	year = {2020},
	month = {07/2020},
	address = {Athens, Greece},
	abstract = {The Fly-Crane is a multi-robot aerial manipulator system composed of three aerial vehicles towed to a platform by means of six cables. This paper presents a method to estimate the mass and the position of the center of mass of a loaded platform (i.e. the Fly-Crane platform including a transported load). The precise knowledge of these parameters allows to sensibly minimize the total effort exerted during a full-pose manipulation task The estimation is based on the measure of the forces applied by the aerial vehicles to the platform in different static configurations. We demonstrate that only two different configurations are sufficient to estimate the inertial parameters. Far-from-ideal numerical simulations show the effectiveness of the estimation method. Once the parameters are estimated, we show the enhancement of the system performances by minimizing the total exerted effort. The validity of the proposed algorithm in non-ideal conditions is presented through simulations based on the Gazebo simulator.},
	doi = {10.1109/ICUAS48674.2020.9213842},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2020h-PetSanTogMilCorFra.pdf},
	author = {Antonio Petitti and Dario Sanalitro and Marco Tognon and A. Milella and Juan Cort{\'e}s and Antonio Franchi}
}
@article {2018q-FraPetRiz,
	title = {Distributed Estimation of State and Parameters in Multi-Agent Cooperative Manipulation},
	journal = {IEEE Trans. on Control of Network Systems},
	volume = {6},
	year = {2019},
	month = {11/2018},
	pages = {690-701},
	abstract = {We present two distributed methods for the estimation of the kinematic parameters, the dynamic parameters, and the kinematic state of an unknown planar body manipulated by a decentralized multi-agent system. The proposed approaches rely on the rigid body kinematics and dynamics, on nonlinear observation theory, and on consensus algorithms. The only three requirements are that each agent can exert a 2D wrench on the load, it can measure the velocity of its contact point, and that the communication graph is connected. Both theoretical nonlinear observability analysis and convergence proofs are provided. The first method assumes constant parameters while the second one can deal with time-varying parameters and can be applied in parallel to any task-oriented control law. For the cases in which a control law is not provided, we propose a distributed and safe control strategy satisfying the observability condition. The effectiveness and robustness of the estimation strategy is showcased by means of realistic MonteCarlo simulations.},
	doi = {10.1109/TCNS.2018.2873153},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2018q-FraPetRiz-preprint.pdf},
	author = {Antonio Franchi and Antonio Petitti and Alessandro Rizzo}
}
@conference {2016b-PetFraDipRiz,
	title = {Decentralized Motion Control for Cooperative Manipulation with a Team of Networked Mobile Manipulators},
	booktitle = {2016 IEEE Int. Conf. on Robotics and Automation},
	year = {2016},
	month = {05/2016},
	pages = {441-446},
	address = {Stockholm, Sweden},
	abstract = { In this paper we consider the cooperative control of the manipulation of a load on a plane by a team of mobile robots. We propose two different novel solutions. The first is a controller which ensures exact tracking of the load twist. This controller is partially decentralized since, locally, it does not rely on the state of all the robots but needs only to know the system parameters and load twist. Then we propose a fully decentralized controller that differs from the first one for the use of i) a decentralized estimation of the parameters and twist of the load based only on local measurements of the velocity of the contact points and ii) a discontinuous robustification term in the control law. The second controller ensures a practical stabilization of the twist in presence of estimation errors. The theoretical results are finally corroborated with a simulation campaign evaluating different manipulation settings.},
	keywords = {Calibration of ground robots, Motion control of multiple robots},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016b-PetFraDipRiz-preprint.pdf , https://homepages.laas.fr/afranchi/robotics/sites/default/files/2016b-PetFraDipRiz.mp4},
	author = {Antonio Petitti and Antonio Franchi and Donato Di Paola and Alessandro Rizzo}
}
@conference {2015b-FraPetRiz,
	title = {Decentralized Parameter Estimation and Observation for Cooperative Mobile Manipulation of an Unknown Load using Noisy Measurements},
	booktitle = {2015 IEEE Int. Conf. on Robotics and Automation},
	year = {2015},
	month = {05/2015},
	pages = {5517-5522},
	address = {Seattle, WA},
	abstract = {In this paper, a distributed approach for the estimation of kinematic and inertial parameters of an unknown rigid body is presented. The body is manipulated by a pool of ground mobile manipulators. Each robot retrieves a noisy measurement of its velocity and the contact forces applied to the body. Kinematics and dynamics arguments are used to distributively estimate the relative positions of the contact points. Subsequently, distributed estimation filters and nonlinear observers are used to estimate the body mass, the relative position between its geometric center and its center of mass, and its moment of inertia. The manipulation strategy is functional to the estimation process, and is suitably designed to satisfy nonlinear observability conditions that are necessary for the success of the estimation. Numerical results corroborate our theoretical findings.},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2015b-FraPetRiz-preprint_0.pdf},
	author = {Antonio Franchi and Antonio Petitti and Alessandro Rizzo}
}
@conference {2014k-FraPetRiz,
	title = {Distributed Estimation of the Inertial Parameters of an Unknown Load via Multi-Robot Manipulation},
	booktitle = {53rd IEEE Conference on Decision and Control},
	year = {2014},
	month = {12/2014},
	pages = {6111-6116},
	address = {Los Angeles, CA},
	abstract = {In this paper, we propose a distributed strategy for the estimation of the kinematic and inertial parameters of an unknown body manipulated by a team of mobile robots. We assume that each robot can measure its own velocity, as well as the contact forces exerted during the body manipulation, but neither the accelerations nor the positions of the contact points are directly accessible. Through kinematics and dynamics arguments, the relative positions of the contact points are estimated in a distributed fashion, and an observability condition is defined. Then, the inertial parameters (i.e., mass, relative position of the center of mass and moment of inertia) are estimated using distributed estimation filters and a nonlinear observer in cooperation with suitable control actions that ensure the observability of the parameters. Finally, we provide numerical simulations that corroborate our theoretical analysis.},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2014k-FraPetRiz-preprint.pdf},
	author = {Antonio Franchi and Antonio Petitti and Alessandro Rizzo}
}
