@article {75, title = {Full-Pose Manipulation Control of a Cable-Suspended Load With Multiple UAVs Under Uncertainties}, journal = {IEEE Robotics and Automation Letters}, volume = {5}, year = {2020}, month = {2020/01}, pages = {2185-2191}, abstract = {

In this work we propose an uncertainty-aware controller for the Fly-crane system, a statically rigid cable-suspended aerial manipulator using the minimum number of aerial robots and cables. The force closure property of the Fly-crane makes it ideal for applications where high precision is required and external disturbances should be compensated. The proposed control requires the knowledge of the nominal values of a minimum number of uncertain kinematic parameters, thus simplifying the identification process and the controller implementation. We propose an optimization-based tuning method of the control gains that ensures stability despite parameter uncertainty and maximizes the H$\infty$ performance. The validity of the proposed framework is shown through real experiments.

}, keywords = {aerial robotic manipulation, cable-suspended aerial manipulator, cable-suspended load, fly-crane system, full-pose manipulation control, multi-robot systems, uncertainty-aware controller}, issn = {2377-3766}, doi = {10.1109/LRA.2020.2969930}, author = {Dario Sanalitro and Heitor J. Savino and Marco Tognon and Juan Cort{\'e}s and Antonio Franchi} } @conference {97, title = {Inertial Estimation and Energy-Efficient Control of a Cable-suspended Load with a Team of UAVs}, booktitle = {2020 International Conference on Unmanned Aircraft Systems (ICUAS)}, year = {2020}, month = {2020/09}, publisher = {IEEE}, organization = {IEEE}, 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.

}, author = {Aantonio Petitti and Dario Sanalitro and Marco Tognon and Annalisa Milella and Juan Cort{\'e}s and Antonio Franchi} } @article {72, title = {Cooperative Aerial Load Transportation via Sampled Communication}, journal = {IEEE Control Systems Letters}, volume = {4}, year = {2019}, note = {

Also selected for presentation at the 2019\ IEEE Conf. on Decision and Control, Nice, France.

}, month = {06/2019}, pages = {277-282}, abstract = {

In this letter, we propose a feedback-based motion planner for a class of multi-agent manipulation systems with a sparse kinematics structure. In other words, the agents are coupled together only by the transported object. The goal is to steer the load into a desired configuration. We suppose that a global motion planner generates a sequence of desired configurations that satisfy constraints as obstacles and singularities avoidance. Then, a local planner receives these references and generates the desired agents velocities, which are converted into force inputs for the vehicles. We focus on the local planner design both in the case of continuously available measurements and when they are transmitted to the agents via sampled communication. For the latter problem, we propose two strategies. The first is the discretization of the continuous-time strategy that preserves stability and guarantees exponential convergence regardless of the sampling period. In this case, the planner gain is static and computed off-line. The second strategy requires to collect the measurements from all sensors and to solve online a set of differential equations at each sampling period. However, it has the advantage to provide doubly exponential convergence. Numerical simulations of these strategies are provided for the cooperative aerial manipulation of a cable-suspended load.

}, keywords = {cable-suspended load, cooperative aerial manipulation, decentralized controller, motion control, multi-robot systems, sampled measurements}, issn = {2475-1456}, doi = {10.1109/LCSYS.2019.2924413}, author = {Enrica Rossi and Marco Tognon and Ruggero Carli and Luca Schenato and Juan Cort{\'e}s and Antonio Franchi} } @article {71, title = {A Truly-Redundant Aerial Manipulator System With Application to Push-and-Slide Inspection in Industrial Plants}, journal = {IEEE Robotics and Automation Letters}, volume = {4}, year = {2019}, month = {01/2019}, pages = {1846-1851}, abstract = {

We present the design, motion planning, and control of an aerial manipulator for non-trivial physical interaction tasks, such as pushing while sliding on curved surfaces-a task which is motivated by the increasing interest in autonomous non-destructive tests for industrial plants. The proposed aerial manipulator consists of a multidirectional-thrust aerial vehicle-to enhance physical interaction capabilities-endowed with a 2-DoFs lightweight arm-to enlarge its workspace. This combination makes it a trulyredundant manipulator going beyond standard aerial manipulators based on collinear multirotor platforms. The controller is based on a PID method with a {\textquotedblleft}displaced{\textquotedblright} positional part that ensures asymptotic stability despite the arm elasticity. A kinodynamic task-constrained and control-aware global motion planner is used. Experiments show that the proposed aerial manipulator system, equipped with an Eddy current probe, is able to scan a metallic pipe sliding the sensor over its surface and preserving the contact. From the measures, a weld on the pipe is successfully detected and mapped.

}, keywords = {aerial manipulator, contact-based inspection, dexterous manipulators, motion control, motion planning}, issn = {2377-3766}, doi = {10.1109/LRA.2019.2895880}, author = {Marco Tognon and Hermes A. Tello-Chavez and Enrico Gasparin and Quentin Sabl{\'e} and Davide Bicego and Anthony Mallet and Marc Lany and Gilles Santi and Bernard Revaz and Juan Cort{\'e}s and Antonio Franchi} } @article {70, title = {Control-Aware Motion Planning for Task-Constrained Aerial Manipulation}, journal = {IEEE Robotics and Automation Letters, Special Issue on Aerial Manipulation}, volume = {3}, year = {2018}, note = {

Also selected for presentation at the 2018 IEEE Int. Conf. on Robotics and Automation, Brisbane , Australia

}, month = {07/2018}, pages = {2478-2484}, abstract = {

This letter presents a new method to address the problem of task-constrained motion planning for aerial manipulators. We propose a control-aware planner based on the paradigm of tight coupling between planning and control. Such paradigm is especially useful in aerial manipulation, where the separation between planning and control is not advisable. The proposed sampling based motion planner uses a controller composed of a second-order inverse kinematics algorithm and a dynamic tracker, as a local planner, thus allowing a more natural consideration of the closed-loop system dynamics. For task-constrained motions, this method let us to sample directly in the reduced and more relevant task space, predict the behavior of the controller avoiding motions that bring to singularities or large tracking errors, and guarantee the correct execution of the maneuver. The method is tested in simulation for a multidirectional-thrust vehicle endowed with a 2-DoF manipulator. The proposed approach is very general, and could be applied to ground and underwater robotic systems to perform manipulation or inspection tasks.

}, keywords = {aerial manipulator, control-aware motion planning, task-constrained motions}, issn = {2377-3766}, doi = {10.1109/LRA.2018.2803206}, author = {Marco Tognon and Elisabetta Cataldi and Hermes A. Tello-Chavez and Gianluca Antonelli and Juan Cort{\'e}s and Antonio Franchi} }