@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}
}
@article {2013i-CenFraMarOri,
	title = {Simultaneous Calibration of Odometry  and Sensor Parameters for Mobile Robots},
	journal = {IEEE Transaction on Robotics},
	volume = {29},
	year = {2013},
	month = {04/2013},
	pages = {475-492},
	abstract = {Consider a differential-drive mobile robot equipped with an on-board exteroceptive sensor that can estimate its own motion, e.g., a range-finder. Calibration of this robot involves estimating six parameters: three for the odometry (radii and distance between the wheels), and three for the pose of the sensor with respect to the robot. After analyzing the observability of this problem, this paper describes a method for calibrating all parameters at the same time, without the need for external sensors or devices, using only the measurement of the wheels velocities and the data from the exteroceptive sensor. The method does not require the robot to move along particular trajectories. Simultaneous calibration is formulated as a maximum-likelihood problem and the solution is found in a closed form. Experimental results show that the accuracy of the proposed calibration method is very close to the attainable limit given by the Cram{\`e}r{\textendash}Rao bound.},
	keywords = {Calibration, Calibration of ground robots, Estimation},
	attachments = {https://homepages.laas.fr/afranchi/robotics/sites/default/files/2013i-CenFraMarOri.pdf},
	author = {Andrea Censi and Antonio Franchi and Luca Marchionni and Giuseppe Oriolo}
}
