Fabio Ruggiero

Exploiting redundancy in Cartesian impedance control of UAVs equipped with a robotic arm

A Cartesian impedance control for UAVs equipped with a robotic arm is presented in this paper. A dynamic relationship between generalized external forces acting on the structure and the system motion, which is specified in terms of Cartesian space coordinates, is provided. Through a suitable choice of such variables and with respect to a given task, thanks to the added degrees of freedom given by the robot arm attached to the UAV, it is possible to exploit the redundancy of the system so as to perform some useful subtasks. The hovering control of a quadrotor, equipped with a 3-DOF robotic arm and subject to contact forces and external disturbances acting on some points of the whole structure, is tested in a simulated case study.

Visual Grasp Planning for Unknown Objects Using a Multifingered Robotic Hand

A method for fast visual grasping of unknown objects with a multifingered robotic hand is presented in this paper. The algorithm is composed of an object surface reconstruction algorithm and a local grasp planner, evolving in parallel. The reconstruction algorithm makes use of images taken by a camera carried by the robot arm. A virtual elastic reconstruction surface is placed around the object. The surface shrinks toward the object until some points intercept the object visual hull. Then, attractive forces with respect to the border of the visual hull are generated so as to compensate for the elastic forces: when an equilibrium between those forces is reached, the surface takes the form of the object shape. Running in parallel to the reconstruction algorithm, the grasp planner moves the fingertips on the current available reconstruction surface, toward points which are optimal (in a local sense) with respect to a number of indices weighting both the grasp quality and the kinematics configuration of the hand. This method, referred to as parallel visual grasp, may represent a valid candidate for applications where online grasp planning is required. A number of experiments are presented, showing the effectiveness of the proposed approach.

Cartesian Impedance Control of a UAV with a Robotic Arm

Abstract The dynamic model of a UAV with an attached robotic arm is derived in a symbolic matrix form through the Euler-Lagrangian formalism. A Cartesian impedance control, which provides a dynamic relationship between external generalized forces acting on the structure and the system motion, is then designed. The hovering control of a quadrotor, equipped with a 3-DOF robotic arm and subject to contact forces and external disturbances, is tested in a simulated case study.

A multilayer control for multirotor UAVs equipped with a servo robot arm

A multilayer architecture to control multirotor UAVs equipped with a servo robot arm is proposed in this paper. The main purpose is to control the aerial platform taking into account the presence of the moving manipulator. Three layers are considered in this work. First, a novel mechanism is proposed considering a moving battery to counterweight the statics of the robotic arm. Then, in order to overcome the mechanical limitations of the previous layer, the residual of the arm static effects on the UAV is computed and compensated through the given control thrust and torques. Finally, an estimator of external forces and moments acting on the aerial vehicle is considered and the estimations are fed back to the controller to compensate neglected aerodynamic effects and the arm dynamics. The performance of the proposed architecture has been experimentally evaluated.

Impedance control of VToL UAVs with a momentum-based external generalized forces estimator

An estimator of external generalized forces (force plus moments) acting on aerial platforms, and based on the momentum of the mechanical system, is proposed for the control of VToL UAVs together with a hierarchical architecture separating the translational and rotational dynamics of the vehicle. The closed-loop system equations are shaped as mechanical impedances, programmable through the controller gains, and forced by the residuals given by the estimation error. This arrangement allows the VToL UAVs to perform hovering and tracking tasks without a precise knowledge of the vehicle dynamics and in presence of external disturbances and unmodeled aerodynamic effects. Experiments are presented to evaluate the performance of the proposed control design.

Emergency landing for a quadrotor in case of a propeller failure: A backstepping approach

A backstepping approach is proposed in this paper to cope with the failure of a quadrotor propeller. The presented methodology supposes to turn off also the motor which is opposite to the broken one. In this way, a birotor configuration with fixed propellers is achieved. The birotor is controlled to follow a planned emergency landing trajectory. Theory shows that the birotor can reach any point in the Cartesian space losing the possibility to control the yaw angle. Simulation tests are employed to validate the proposed controller design.

Control of Nonprehensile Rolling Manipulation: Balancing a Disk on a Disk

This paper presents feedback stabilization control of a rolling manipulation system called the disk-on-disk. The system consists of two disks in which the upper disk (object) is free to roll on the lower disk (hand) under the influence of gravity. The goal is to stabilize the object at the unstable upright position directly above the hand. We show that it is possible to stabilize the object at the upright position, while the hand or object rotates to a specific orientation or spins at a constant velocity. We use full-state feedback linearization to derive control laws. We present simulation as well as experimental results demonstrating the controllers.

Robotic Ball Catching with an Eye-in-Hand Single-Camera System

In this paper, a unified control framework is proposed to realize a robotic ball catching task with only a moving single-camera (eye-in-hand) system able to catch flying, rolling, and bouncing balls in the same formalism. The thrown ball is visually tracked through a circle detection algorithm. Once the ball is recognized, the camera is forced to follow a baseline in the space so as to acquire an initial dataset of visual measurements. A first estimate of the catching point is initially provided through a linear algorithm. Then, additional visual measurements are acquired to constantly refine the current estimate by exploiting a nonlinear optimization algorithm and a more accurate ballistic model. A classic partitioned visual servoing approach is employed to control the translational and rotational components of the camera differently. Experimental results performed on an industrial robotic system prove the effectiveness of the presented solution. A motion-capture system is employed to validate the proposed estimation process via ground truth.

Grasping and Control of Multi-Fingered Hands

An important issue in controlling a multi-fingered robotic hand grasping an object is the evaluation of the minimal contact forces able to guarantee the stability of the grasp and its feasibility. This problem can be solved online if suitable sensing information is available. In detail, using finger tactile information and contact force measurements, an efficient algorithm is developed to compute the optimal contact forces, assuming that, during the execution of a manipulation task, both the position of the contact points on the object and the wrench to be balanced by the contact forces may change with time. Since manipulation systems can be redundant also if the single fingers are not –due to the presence of the additional degrees of freedom (DOFs) provided by the contact variables– suitable control strategies taking advantage of such redundancy are adopted, both for single and dual-hand manipulation tasks. Another goal pursued in DEXMART is the development of a human-like grasping approach inspired to neuroscience studies. In order to simplify the synthesis of a grasp, a configuration subspace based on few predominant postural synergies of the robotic hand is computed. This approach is evaluated at kinematic level, showing that power and precise grasps can be performed using up to the third predominant synergy.

Grasp planning and parallel control of a redundant dual-arm/hand manipulation system

SUMMARY In this paper, a kinematic model of a dual-arm/hand robotic system is derived, which allows the computation of the object position and orientation from the joint variables of each arm and each finger as well as from a suitable set of contact variables. On the basis of this model, a motion planner is designed, where the kinematic redundancy of the system is exploited to satisfy some secondary tasks aimed at ensuring grasp stability and manipulation dexterity without violating physical constraints. To this purpose, a prioritized task sequencing with smooth transitions between tasks is adopted. Afterwards, a controller is designed so as to execute the motion references provided by the planner and, at the same time, achieve a desired contact force exerted by each finger on the grasped object. To this end, a parallel position/force control is considered. A simulation case study has been developed by using the dynamic simulator GRASPIT!, which has been suitably adapted and redistributed.