A decentralized strategy for object transportation is presented, assuming that the object is grasped by a team of N cooperative manipulators. The proposed strategy consists of two steps. First, each robot estimates the wrenches applied to the object by all the others robots, even without all-to-all communication. Second, an admittance control scheme is used to limit internal wrenches, preventing excessive stresses that could affect manipulation stability and object integrity. Stability is proven under the assumption of a spring connection between each robot end-effector and its grasping point on the object. A work cell with two 7-degree-of-freedom (DOF) and one 6-DOF robotic manipulators was used to validate the strategy. Experimental results show that the controller effectively reduces internal wrenches, confirming the feasibility and robustness of the decentralized approach in cooperative manipulation.

In this paper, a novel decentralized leader-follower control scheme for multi-agent systems is devised, where each agent communicates only with a subset of neighboring mates. The goal is to track assigned trajectories for the centroid and the formation of the system. The desired trajectories are known only by a subset of agents, named leaders: the other agents, the followers, are required to estimate the desired trajectories based on a dynamic consensus scheme. Then, the desired trajectories to be tracked by each agent are computed from the estimated trajectories for the centroid and the formation and a simple local control loop is adopted to track the former. Stability and performance are analyzed and experiments are run on Robotarium platform to show the effectiveness of the approach and the effect of different parameters on the achieved performance.

In this paper an experimental study of set-based task-priority kinematic control for a dual-arm mobile robot is developed. The control strategy for the coordination of the two manipulators and the mobile base relies on the definition of a set of elementary tasks to be properly handled depending on their functional role. In particular, the tasks have been grouped into three categories: safety, operational and optimization tasks. The effectiveness of the resulting task hierarchy has been validated through experiments on a Kinova Movo robot, in a domestic use case scenario.

This paper presents a method to cope with autonomous assembly tasks in the presence of uncertainties. To this aim, a Peg-in-Hole operation is considered, where the target workpiece position is unknown and the peg-hole clearance is small. Deep learning based hole detection and 3D surface reconstruction techniques are combined for accurate workpiece localization. In detail, the hole is detected by using a convolutional neural network (CNN), while the target workpiece surface is reconstructed via 3D-Digital Image Correlation (3D-DIC). Peg insertion is performed via admittance control that confers the suitable compliance to the peg. Experiments on a collaborative manipulator confirm that the proposed approach can be promising for achieving a better degree of autonomy for a class of robotic tasks in partially structured environments.

The paper presents a multiple task-priority inverse kinematics algorithm for a dual-arm aerial manipulator. Both tasks defined as equality constraints and inequality constraints are handled by means of a singularity robust method based on the Null-Space based Behavioral control. The proposed schema is constituted by the inverse kinematics control, that receives the desired behavior of the system and outputs the reference values for the motion variables, i.e. the UAV pose and the arm joints position, and a motion control, that computes the vehicle thrusts and the joint torques. The method has been experimentally validated on a system composed by an underactuated aerial hexarotor vehicle equipped with two lightweight 4-DOF manipulators, involved in operations requiring the coordination of the two arms and the vehicle.

This paper presents the design, control, and experimental validation of a novel fully-actuated aerial robot for physically interactive tasks, named Tilt-Hex. We show how the Tilt-Hex, a tilted-propeller hexarotor is able to control the full pose (position and orientation independently) using a geometric control, and to exert a full-wrench (force and torque independently) with a rigidly attached end-effector using an admittance control paradigm. An outer loop control governs the desired admittance behavior and an inner loop based on geometric control ensures pose tracking. The interaction forces are estimated by a momentum based observer. Control and observation are made possible by a precise control and measurement of the speed of each propeller. An extensive experimental campaign shows that the Tilt-Hex is able to outperform the classical underactuated multi-rotors in terms of stability, accuracy and dexterity and represent one of the best choice at date for tasks requiring aerial physical interaction.

In this paper a three layer control architecture for multiple aerial robotic manipulators is presented. The top layer, on the basis of the desired mission, determines the end-effector desired trajectory for each manipulator, while the middle layer is in charge of computing the motion references in order to track such end-effectors trajectories coming from the upper layer. Finally the bottom layer is a low level motion controller, which tracks the motion references. The overall mission is decomposed in a set of elementary behaviors which are combined together, through the Null Space-based Behavioral (NSB) approach, into more complex compounds behaviors. The proposed framework has been tested conducting an experimental campaign.

In this paper, an impedance control scheme for aerial robotic manipulators is proposed, with the aim of reducing the end-effector interaction forces with the environment. The proposed control has a multi-level architecture, in detail the outer loop is composed by a trajectory generator and an impedance filter that modifies the trajectory to achieve a complaint behaviour in the end-effector space; a middle loop is used to generate the joint space variables through an inverse kinematic algorithm; finally the inner loop is aimed at ensuring the motion tracking. The proposed control architecture has been experimentally tested.

This work tackles the problem of controlling an Unmanned Aerial Vehicle equipped with a robotic Manipulator and it has been developed within the framework of the EU-funded ARCAS (Aerial Robotics Cooperative Assembly System) project. A behavioral control, based on the Null Space-based Behavioral (NSB) paradigm, is proposed to tackle the coordination between the arm and vehicle motions. To this aim, a set of basic functionalities (called elementary behaviors) are designed and combined in a priority order to attain complex tasks (called compound behaviors). The proposed controller has been experimentally validated on a multirotor aircraft with an attached 6 Degree of Freedoms manipulator. Two experimental case studies, involving several compound behaviors, have been reported and the results show the effectiveness of the approach.

In this paper, an impedance control scheme for cooperative quadrotors with robotic arms is proposed in order to limit both the contact forces, due to the object/environment interaction, and the internal forces, due to the manipulators/ object interaction. To this aim, two impedance filters are used to determine the reference trajectories for manipulator end effectors: the first is aimed at conferring a compliant behavior at the object level (external impedance), while the second filter, is aimed at avoiding large internal loading of the object (internal impedance). Such trajectories are fed to a motion controller including an inverse kinematics algorithm and a PD controller with gravity compensation. The effectiveness of the proposed approach is then verified in simulation.

In this paper, a decentralized control strategy for networked multi-robot systems that allows the tracking of the team centroid and the relative formation is presented. The proposed solution consists of a distributed observer-controller scheme where, based only on local information, each robot estimates the collective state and tracks the two assigned control variables. We provide a formal stability analysis of the observer-controller scheme and we relate convergence properties to the topology of the connectivity graph. Experiments are presented to validate the approach.

In this paper a decentralized controller-observer scheme for centroid tracking with a multi-robot system is presented. The key idea is to develop, for each robot, an observer of the collective system's state; each local observer is updated by only using information of the state of the robot and of its neighbors. The local observers' estimations are then used by the individual robots to cooperatively track an assigned time-varying reference for the weighted centroid. Convergence of the scheme is proven for both fixed and switching communication topologies, as well as for directed and undirected communication graphs. Numerical simulations relative to different case studies are illustrated to validate the approach.

In this paper, a kinematic model for motion coordination and control of a redundant robotic dual-arm/hand system is derived, which allows to compute the object pose from the joint variables of each arm and each finger as well as from a suitable set of contact variables. This model is used to design a two-stage control scheme to achieve a desired object motion and maintain desired normal contact forces applied to the object. Several secondary tasks are accomplished through a prioritized task sequencing management of the whole system redundancy. A simulation case study is presented to demonstrate the effectiveness of the proposed approach.

Differential-drive mobile robots are usually equipped with video-cameras for navigation purposes. In order to ensure proper operational capabilities of such systems, several calibration steps are required to estimate the following quantities: the video-camera intrinsic and extrinsic parameters, the relative pose between the camera and the vehicle frame and, finally, the odometric parameters of the vehicle. In this paper the simultaneous estimation of the above mentioned quantities is achieved by a systematic and effective calibration procedure that does not require any iterative step. The calibration procedure needs only on-board measurements given by the wheels encoders, the camera and a number of properly taken camera snapshots of a set of known landmarks. Numerical simulations and experimental results with a mobile robot Khepera III equipped with a low-cost camera confirm the effectiveness of the proposed technique.

This paper proposes a multiple robot control algorithm to approach the problem of patrolling an open or closed line. The algorithm is fully decentralized, i.e., no communication occurs between robots or with a central station. Robots behave according only to their sensing and computing capabilities to ensure high scalability and robustness towards robots' fault. The patrolling algorithm is designed in the framework of behavioral control and it is based on the concept of Action: an higher level of abstraction with respect to the behaviors. Each Action is obtained by combining more elementary behaviors in the Null-Space-Behavioral framework. A Finite-State-Automata is designed as supervisor in charge of selecting the appropriate action. The approach has been validated in simulation as well as experimentally with a patrol of 3 Pioneer robots available at the Distributed Intelligence Laboratory of the University of Tennessee.

An environment for open real-time control of an industrial robotic cell is presented in this paper. The experimental setup is composed of two industrial robot manipulators equipped with force/torque sensors and pneumatic grippers, a vision system and a belt conveyor. The original industrial robot controllers have been replaced by a single PC with software running under a real-time variant of the Linux operative system. The new control environment allows advanced control schemes to be developed and tested for the single robots and for the dual-arm robotic cell, including force control and visual servoing tasks. An advanced user interface and a simulation environment have been developed, which permit fast, safe and reliable prototyping of planning and control algorithms.

In this paper an observer-based fault diagnosis (FD) approach for autonomous underwater vehicles (AUVs), subject to actuator faults (i.e., faults affecting the propulsion system and/or the control surfaces), is proposed. A diagnostic observer is developed based on the available dynamic model of the AUV. Compensation of unknown dynamics, uncertainties and disturbances is achieved through the adoption of a class of neural interpolators (support vector machines, SVMs) trained off line. On the other hand, interpolation of unknown actuator faults is performed by adopting a radial basis function (RBF) network, whose weights are adaptively tuned on line. The effectiveness of the approach is tested in a simulation case study developed for the NPS AUV II (PHOENIX) vehicle.

A novel adaptive control law for the end-effector tracking problem of underwater vehicle-manipulator systems (UVMSs) is presented in this paper. By exploiting the serial-chain kinematic structure of the UVMS, the overall control problem is decomposed in a set of elementary control problems, each of them formulated with respect to a single rigid body in the system. The proposed approach results in a modular control scheme which simplifies application to UVMSs with a large number of links, reduces the required computational burden, and allows efficient implementation on distributed computing architectures. Furthermore, the occurrence of kinematic and representation singularities is overcome, respectively, by expressing the control law in body-fixed coordinates and representing the attitude via the unit quaternion. To show the effectiveness of the proposed control strategy, a simulation case study is developed for a vehicle in spatial motion carrying a six-degree-of-freedom manipulator.

An adaptive control law for autonomous underwater vehicles (AUVs) is presented. Usually, the control laws are designed with respect to a mathematical model expressed either in the Earth-fixed frame or in the vehicle-fixed frame. These two approaches, however, do not take into account the different origin of the effects that can affect the steady state errors: namely, the restoring generalized forces and the ocean current. With the use of a suitable adaptive action those effects can be properly taken into account as is shown in the paper.

Addresses kinematic control of a redundant space manipulator mounted on a free-floating spacecraft. Redundancy of the system with respect to the number of task variables for spacecraft attitude and manipulator end-effector pose is considered. Also, the problem of both spacecraft attitude and end-effector orientation representation is tackled. A nonminimal singularity-free representation of rigid body orientation is adopted: the unit quaternion; this allows avoiding representation singularities and formulating the inverse kinematics algorithms in terms of geometrically meaningful variables. Depending on the nature of the task for the spacecraft/manipulator system, a number of closed-loop inverse kinematics algorithms are proposed. Case studies are developed for a system of a spacecraft with a six-joint manipulator attached.

The goal of the paper is the application of a geometrically consistent impedance concept to control interaction with the environment of a rigid object manipulated by a dual-robot system. A six-DOF impedance is specified at the object level to confer a compliant behavior for both the translational and the rotational motion when an external force and moment occurs at the contact. Geometric consistency is ensured thanks to the use of the unit quaternion to describe object frame orientation. The resulting object motion is decomposed into the equivalent motions at the end effectors of the two robots, via a task-oriented formulation. The control scheme is derived according to an inverse dynamics strategy with adoption of an inner motion loop providing robustness to unmodeled dynamics and disturbances. Experimental results on the two industrial robots available in the lab are discussed.

Focuses on the problem of tracking a desired end-effector position and orientation for a robot manipulator. A nonminimal parameterization of the orientation-the unit quaternion-is used to design the control law. Tracking control typically requires full-state measurements, i.e., end-effector position and orientation as well as linear and angular velocities. However, while position and orientation measurements are available, often velocities have to be estimated. In the paper, an observer-controller scheme is proposed which ensures tracking in the task space without using velocity measurements. The performance of the proposed scheme is evaluated both in simulation and through experimental tests on an industrial robot.

A new approach to 6-DOF impedance control is proposed, where the end-effector orientation displacement is derived from the rotation matrix expressing the mutual orientation between the compliant frame and the desired frame. An alternative Euler angles-based description is proposed which mitigates the effects of representation singularities. Then, a class of angle/axis representations are considered to derive the dynamic equation for the rotational part of a 6-DOF impedance at the end effector, using an energy-based argument. The unit quaternion representation is selected to further analyze the properties of the rotational impedance. The resulting impedance controllers are designed according to an inverse dynamics strategy with contact force and moment measurements, where an inner loop acting on the end-effector position and orientation error is adopted to confer robustness to unmodeled dynamics and external disturbances. Experiments on an industrial robot were carried out, and the results of case studies are discussed.

The adoption of efficient online fault detection and isolation (FDI) tools is becoming of the utmost importance for robots, especially for those operating in remote or hazardous environments, where a high degree of safety and self-diagnostics capabilities is required. In this paper a new observer-based approach to fault detection and isolation for robot manipulators is proposed. A nonlinear observer of the system's outputs, joint position and velocities, is designed directly in the discrete-time domain; in order to improve the robustness of the observer to unknown dynamics and discretization errors, a linear feedback of the observation error and a delayed nonlinear compensation action are added. The residuals for the detection of both sensor and actuator failures are then generated from the observation errors. Simulation results show the effectiveness of the proposed approach, even if a relatively low sampling rate is adopted and in the presence of large modeling errors.