In this article, an optimal controller for achieving constrained admittance control is proposed. This controller strictly adheres to the constraint boundaries while ensuring minimal variations in kinematic energy. The proposed method integrates admittance control for human-robot interaction with the Udwadia-Kalaba equations for constrained motion into a unified framework. The proposed architecture has been tested and validated both with simulations and real tests on a 6-DoF UR5e robot. The results demonstrate that the proposed architecture outperforms virtual fixtures, one of the most commonly used techniques to implement effective path-following control.

Learning by demonstration techniques are gaining popularity within the human-robot collaboration (HRC) scenarios. This is because they allow to deeply exploit the versatility of collaborative robots. In this context, dynamic motion primitives (DMPs) have become a standard method for enabling human operators to easily teach tasks to robots. However, DMPs have two main limitations. First, they may encounter difficulties in generalizing some tasks, which can lead to non-intuitive behavior. Second, it is not guaranteed that the output of DMPs is compliant with ISO/TS 15066, which provides guidelines for assessing safety in collaborative scenarios. This work aims to address these two issues by introducing a novel control pipeline. This pipeline leverages a new variant of DMPs, called Swap DMPs (SDMPs), introduced in this work. The SDMPs enable a more intuitive behavior when the robot reproduces the learned task. Subsequently, SDMPs are encoded into a new optimization problem that ensures the robot complies with the Speed and Separation Monitoring (SSM) collaborative mode. The proposed approach has been experimentally validated and compared with traditional DMPs in both simulation and a real scenario, where a UR5e and a human operator collaborate on a polishing task.

Ensuring safe and effective physical human-robot interaction (pHRI) remains a critical challenge in industrial robotics, particularly in ensuring compliance with ISO/TS 15066 safety standards. This paper proposes a novel framework to achieve a safe and robust physical human-robot interaction (pHRI). The framework adapts the parameters of a variable admittance controller online in order to guarantee passivity and compliance with ISO/TS 15066. Passivity is guaranteed using an energy tank, while a safety constraint explicitly handles the Power and Force Limiting (PFL) energy limit. Experimental validation on an industrial robot demonstrates the effectiveness of the framework.

The integration of robots into shared workspaces alongside humans is the basis of Human-Robot Collaboration (HRC). This field of research has changed the paradigm of the industrial context, making HRC of pivotal importance for both researchers and the industry. In this context, a suitable task scheduling and trajectory planning strategy are crucial to achieve good performances and create a synergy between the two actors. Indeed, the task scheduling should be able to optimally distribute the tasks between the actors and recover from possible failures, i.e. by rescheduling the tasks. The trajectory planning strategy must comply with the safety standards that impose a reduction of velocity based on human behaviour. To this end, the monitoring system must also be safe-certified; otherwise, safety cannot be guaranteed. This paper proposes a novel architecture that integrates a dynamic task scheduling module with a dynamic trajectory planning module that explicitly considers ISO/TS 15066. For this purpose, the framework exploits a secure and certified monitoring system capable of tracking the human operator even in case of occlusions. The overall platform has been extensively validated both in a real and complex industrial scenario within the context of the ROSSINI EU project, where a dual-arm mobile robot collaborates with a human operator in an automatic machine-tending operation, and in a mock-up scenario.

The human-robot collaboration scenarios are characterized by the presence of human operators and robots that work in close contact with each other. As a consequence, the safety regulations have been updated in order to provide guidelines on how to asses safety in these new scenarios. In particular, Power and Force Limiting (PFL) collaborative mode describes how the energy should be regulated during the collaboration. Based on these guidelines, we propose a new optimal trajectory planner which, by exploiting the variability of the robot’s inertia as a function of its configuration, is able to return trajectories that can be travelled at greater speed and in less time, while guaranteeing the safety limits according to the standard. The proposed planner was validated first in simulation, comparing completion times with other state-of-the-art planning algorithms, and then experimentally, demonstrating the performance of the planned trajectories during physical interaction with the environment. Both validations confirm the effectiveness of the proposed planner, which returns shorter completion times while ensuring safe interaction.

In the actual industrial scenarios, human operators and robots work together sharing the workspace. Such proximity requires special attention in ensuring safety for the human operator, which is often translated in collision avoidance behaviour or high speed reduction. Adhering safety however is not the only aspect that must be taken into account. For many tasks, such as welding, it is crucial to ensure that the robot performs exactly the planned path. To optimize robot performance while complying with safety regulations, this work introduces a novel optimal nonlinear control problem. It prioritizes path preservation, exploiting redundancy to minimize task execution time, while explicitly adhering to the constraints imposed by ISO/TS 15066. To achieve high-performance outcomes, the control problem is addressed using the Model Predictive Control (MPC) approach. The proposed strategy has been experimentally validated in both simulations and a real-world industrial task involving a Kuka LWR4+ robot.

In the context of interaction with unmodelled systems, it becomes imperative for a robot controller to possess the capability to dynamically adjust its actions in real-time, enhancing its resilience in the face of fluctuating environmental conditions. This adaptation process must be performed in a stability-preserving fashion, and resourcefully exploit the knowledge acquired during the interaction process. In this article, we propose a novel control strategy, based on the synergistic usage of state-of-the-art passivity-based control and Deep Reinforcement Learning (DRL). The concept of energy tank is used to provide stability guarantees for the interaction controller with uncertain environments, while an online learning policy allows to properly estimate the requirements of the task and adapt the controller accordingly, thus simultaneously achieving stability and performance. The proposed architecture is successfully validated through simulations and experiments with a collaborative manipulator in a surface polishing task.

In the context of Human-Robot Collaboration (HRC), it is crucial that the two actors are able to communicate with each other in a natural and efficient manner. The absence of a communication interface is often a cause of undesired slowdowns. On one hand, this is because unforeseen events may occur, leading to errors. On the other hand, due to the close contact between humans and robots, the speed must be reduced significantly to comply with safety standard ISO/TS 15066. In this paper, we propose a novel architecture that enables operators and robots to communicate efficiently, emulating human-to-human dialogue, while addressing safety concerns. This approach aims to establish a communication framework that not only facilitates collaboration but also reduces undesired speed reduction. Through the use of a predictive simulator, we can anticipate safety-related limitations, ensuring smoother workflows, minimizing risks, and optimizing efficiency. The overall architecture has been validated with a UR10e and compared with a state of the art technique. The results show a significant improvement in user experience, with a corresponding 23% reduction in execution times and a 50% decrease in robot downtime.

This paper presents a Human-Robot Blind Handover architecture within the context of Human-Robot Collaboration (HRC). The focus lies on a blind handover scenario where the operator is intentionally faced away, focused in a task, and requires an object from the robot. In this context, it is imperative for the robot to autonomously manage the entire handover process. Key considerations include ensuring safety while handing the object to the operator’s hand, and detect the proper timing to release the object. The article explores strategies to navigate these challenges, emphasizing the need for a robot to operate safely and independently in facilitating blind handovers, thereby contributing to the advancement of HRC protocols and fostering a natural and efficient collaboration between humans and robots.

Energy tanks have gained popularity inside the robotics and control communities over the last years, since they represent a formidable tool to enforce passivity (and, thus, input/output stability) of a controlled robot, possibly interacting with uncertain environments. One weak point of passification strategies based on energy tanks concerns, however, their initialization. Indeed, a too large initial energy can cause practical unstable behaviors, while a too low initial energy level can prevent the correct execution of the task. This shortcoming becomes even more relevant in presence of uncertainties in the robot model and/or environment, since it may be hard to predict in advance the correct (safe) amount of initial tank energy for a successful task execution. In this paper we then propose a new strategy for addressing this issue. The recent notion of closed-loop state sensitivity is exploited to derive precise bounds (tubes) on the tank energy behavior by assuming parametric uncertainty in the robot model. These tubes are then exploited in a novel nonlinear optimization problem aiming at finding both the best trajectory and the minimal initial tank energy that allow executing a positioning task for any value of the uncertain parameters in a given range. The approach is finally validated via a statistical analysis in simulation and experiments on real robot hardware.

Recent advances in robotics have allowed the introduction of robots assisting and working together with human subjects. To promote their use and diffusion, intuitive and user-friendly interaction means should be adopted. In particular, gestures have become an established way to interact with robots since they allow to command them in an intuitive manner. In this article, we focus on the problem of gesture recognition in human–robot interaction (HRI). While this problem has been largely studied in the literature, it poses specific constraints when applied to HRI. We propose a framework consisting in a pipeline devised to take into account these specific constraints. We implement the proposed pipeline considering, as an example, an evaluation use case. To this end, we consider standard machine learning algorithms for the classification stage and evaluate their performance considering different performance metrics for a thorough assessment.

In this paper we present a novel strategy for reactive collision-free feasible motion planning for robotic manipulators operating inside an environment populated by moving obstacles. The proposed strategy embeds the Dynamical System (DS) based obstacle avoidance algorithm into a constrained non-linear optimization problem following the Model Predictive Control (MPC) approach. The solution of the problem allows the robot to avoid undesired collision with moving obstacles ensuring at the same time that its motion is feasible and does not overcome the designed constraints on velocity and acceleration. Simulations demonstrate that the introduction of the MPC prediction horizon helps the optimization solver in finding the solution leading to obstacle avoidance in situations where a non predictive implementation of the DS-based method would fail. Finally, the proposed strategy has been validated in an experimental work-cell using a Franka-Emika Panda robot.

A fruitful collaboration is based on the mutual knowledge of each other skills and on the possibility of communicating their own limits and proposing alternatives to adapt the execution of a task to the capabilities of the collaborators. This paper aims at reproducing such a scenario in a human-robot collaboration setting by proposing a novel communication control architecture. Exploiting control barrier functions, the robot is made aware of its (dynamic) skills and limits and, thanks to a local predictor, it is able to assess if it is possible to execute a requested task and, if not, to propose alternative by relaxing some constraints. The controller is interfaced with a communication infrastructure that enables human and robot to set up a bidirectional communication about the task to execute and the human to take an informed decision on the behavior of the robot. A comparative experimental validation is proposed.

During physical human robot collaboration, it is important to be able to implement a time-varying interactive behaviour while ensuring robust stability. Admittance control and passivity theory can be exploited for achieving these objectives. Nevertheless, when the admittance dynamics is time-varying, it can happen that, for ensuring a passive and stable behaviour, some spurious dissipative effects have to be introduced in the admittance dynamics. These effects are perceived by the user and degrade the collaborative performance. In this paper we exploit the task redundancy of the manipulator in order to harvest energy in the null space and to avoid spurious dynamics on the admittance. The proposed architecture is validated by simulations and by experiments onto a collaborative robot.

In this paper, we propose a novel torque controller for the implementation virtual remote center of motion. The controller allows the system to implement the required behavior and guarantees the satisfaction of the remote center of motion constraint. Exploiting the Udwadia-Kalaba equation for constrained dynamic systems, the controller is synthesized considering the dynamic effect the constraint produces on the manipulator, achieving more effective control with respect to kinematic strategies, and allowing the implementation of compliance behaviors. Simulations and experimental validation with a KUKA LWR 4+ with 7 degrees of freedom has been performed to check the performances of the proposed controller. Results show the effectiveness of the proposed controller with different control action, and the capability to interact with the environment by implementing compliant motion control.

Within the context of Robotic Minimally Invasive Surgery (R-MIS), we propose a novel linear model predictive controller formulation for the coordination of multiple autonomous robotic arms. The controller is synthesized by formulating a linear approximation of non-linear constraints, which allows the controller to be both computationally faster and better performing due to the increased prediction horizon allowed within the real-time control requirements for the proposed surgical application. The solution is validated under the expected constraints of a surgical scenario in which multiple laparoscopic tools must move and coordinate in a shared environment.

In robotic applications where the autonomy is shared between the human and the robot, the autonomous behavior of the robotic system is determined considering mainly the task to be executed and the data collected from the environment using, e.g., formal methods and machine learning techniques. Nevertheless, it is important to correctly translate high-level decision into low-level control inputs in order to avoid an unstable behavior due to a naive implementation of the autonomy. In this article, we propose an energy-based architecture for shared autonomy that allows to reproduce as closely as possible the desired behavior, while ensuring a robust stability of the robotic system. The proposed architecture is experimentally validated in two application scenarios: shared control of a multirobot system and variable admittance control in human robot collaboration

In Human-Robot Collaboration, the robot operates in a highly dynamic environment. Thus, it is pivotal to guarantee the robust stability of the system during the interaction but also a high flexibility of the robot behavior in order to ensure safety and reactivity to the variable conditions of the collaborative scenario.In this paper we propose a control architecture capable of maximizing the flexibility of the robot while guaranteeing a stable behavior when physically interacting with the environment. This is achieved by combining an energy tank based variable admittance architecture with control barrier functions. The proposed architecture is experimentally validated on a collaborative robot.

In this paper, we propose a novel bilateral teleoperation architecture that allows to optimally render the remote interaction force at the local side while guaranteeing a robustly stable behaviour. Stability is guaranteed by ensuring a proper energy exchange between the local and the remote sides. Desired performance is obtained by optimizing the way energy is exploited for generating the behaviour at each side. The effectiveness of the proposed architecture is experimentally validated on a torque-controlled manipulator and in a surgical scenario, using the da Vinci®Research Kit (dVRK).

In this paper we propose a novel flexible and optimization-free controller for standard torque-controlled manipulator for Robotic-Assisted Minimally Invasive Surgery. A novel method has been developed to model the constraint introduced by the laparoscopic tool, i.e. the remote center of motion, exploiting closed chain manipulators theory, and the final controller was synthesized considering the effects the constraint produces at a dynamic level. A set of simulations has been performed in a trajectory tracking task to validate the performances of the proposed controller. Performances have been also tested in a real experimental scenario with a KUKA LWR 4+ with 7 degrees of freedom endowed with a laparoscopic-like tool. Results show the effectiveness of the proposed controller and its capability of modifying the trajectory in order to preserve the RCM constraint.

In collaborative robotic applications, human and robot have to work together to accomplish a common job, composed by a set of tasks. In order to achieve an efficient human-robot collaboration (HRC), it is important to have an integration between a proper task scheduling strategy and a task execution strategy. The first must deal with the variability of the two agents, while the second must deal with the safety standards. In this paper, we propose an integrated architecture for task scheduling and execution in a collaborative cell. The tasks are dynamically scheduled handling the uncertainity in both the human and the robot behaviors. Subsequently, at the execution level, the task is accomplished computing trajectories comply with the safety regulations. The planning information are mutually integrated in real-time with the scheduling procedure in order improve the HRC.

In the present paper, we propose a novel system-driven adaptive shared control framework in which the autonomous system allocates the authority among the human operator and itself. Authority allocation is based on a metric derived from a Bayesian filter, which is being adapted online according to real measurements. In this way, time-varying measurement noise characteristics are incorporated. We present the stability proof for the proposed shared control architecture with adaptive authority allocation, which includes time delay in the communication channel between the operator and the robot. Furthermore, the proposed method is validated through experiments and a user-study evaluation. The obtained results indicate significant improvements in task execution compared with pure teleoperation.

Executing multiple tasks concurrently is important in many robotic applications. Moreover, the prioritization of tasks is essential in applications where safety-critical tasks need to precede application-related objectives, in order to protect both the robot from its surroundings and vice versa. Furthermore, the possibility of switching the priority of tasks during their execution gives the robotic system the flexibility of changing its objectives over time. In this paper, we present an optimization-based task execution and prioritization framework that lends itself to the case of time-varying priorities as well as variable number of tasks. We introduce the concept of extended set-based tasks, encode them using control barrier functions, and execute them by means of a constrained-optimization problem, which can be efficiently solved in an online fashion. Finally, we show the application of the proposed approach to the case of a redundant robotic manipulator.

Multi-robot systems are able to achieve common objectives exchanging information among each other. This is possible exploiting a communication structure, usually modeled as a graph, whose topological properties (such as connectivity) are very relevant in the overall performance of the multirobot system. When considering mobile robots, such properties can change over time: robots are then controlled to preserve them, thus guaranteeing the possibility, for the overall system, to achieve its goals. This, however, implies limitations on the possible motion patterns of the robots, thus reducing the flexibility of the overall multi-robot system. In this paper we introduce teleoperation as a means to reduce these limitations, allowing temporary violations of topological properties, with the aim of increasing the flexibility of the multi-robot system.

In this paper we present a novel strategy for motion planning of autonomous robotic arms in Robotic Minimally Invasive Surgery (R-MIS). We consider a scenario where several laparoscopic tools must move and coordinate in a shared environment. The motion planner is based on a Model Predictive Controller (MPC) that predicts the future behavior of the robots and allows to move them avoiding collisions between the tools and satisfying the velocity limitations. In order to avoid the local minima that could affect the MPC, we propose a strategy for driving it through a sequence of waypoints. The proposed control strategy is validated on a realistic surgical scenario.

This article proposes a passivity-based approach for simulating satellite dynamics on a position-controlled robot equipped with a force-torque sensor. Time delays intrinsic in the computational loop and discrete-time integration degrade the behavior of the satellite dynamics reproduced by the robot. These factors can generate an energy-inconsistent simulation and can even render the system unstable. In this article, time delay and discrete-time integration effects are analyzed from an energetic perspective and compensated through a passivity-based control strategy to ensure a faithful and stable dynamic simulation with position-controlled robots. The benefit of the proposed strategy is validated by simulations and experiments on the On-Orbit Servicing Simulator (OOS-SIM), a robotic facility used for simulating free-floating dynamics.

Collaborative robots are one of the key drivers in Industry 4.0 and they have evolved considerably since the last decades of the 20th century. With respect to the industrial robots, collaborative robots are more productive, flexible, versatile and safer. In the recent years, many industrial robot producers and startups entered the segment of collaborative robots. In this paper, we propose a methodology for developing a comparative analysis of the collaborative robots currently available in the market. The goal of the paper is to provide a framework for allowing the benchmarking, based on common robot parameters and standardized experiments that can be performed with the robot under investigation. An experimental technological review of three different collaborative robots is provided, to show how the methodology can be applied in real cases.

In this paper, a two-layer architecture for the bilateral teleoperation of multi-arms systems with communication delay is presented. We extend the single-master-single-slave two layer approach proposed in [1] by connecting multiple robots to a single energy tank. This allows to minimize the conservativeness due to passivity preservation and to increment the level of transparency that can be achieved. The proposed approach is implemented on a realistic surgical scenario developed within the EU-funded SARAS project.

Performing ultrasound procedures from a remote site is a challenging task since both a stable behavior, for the safety of the patient, and a high-level of usability, to exploit the sonographer's expertise, need to be guaranteed. Furthermore, a teleoperation system that provides such requirements has to deal with communication delays as well. To address this issue, we use the two-layer algorithm: a passivity-based bilateral teleoperation architecture able to guarantee stability despite unknown and time-varying delay. Its flexibility allows to implement different kinds of control laws. In a Tele-Echography system, the slave manipulator has to apply significant forces needed by the procedure whereas the haptic device at the master side should be very light to avoid tiring the operator. Therefore, the energy needed by these two robots to perform their movements is very different and the energy injected into the system by the operator is often not sufficient to implement the desired action at the slave side. Methods to overcome this problem require to perfectly know the dynamical models of the robots. The solution proposed in this paper does not require such knowledge and is based on properly scaling the energy exchanged between the master and the slave side. We show the effectiveness of this approach in a real setup using a TOUCH haptic device and a WAM Barrett robot holding an ultrasound probe.

The possibility of adapting online the way a robot interacts with the environment is becoming more and more important. In this paper we introduce the tank based admittance controller. We show that all the admittance controllers can be modeled as an energy optimization problem and then we introduce a novel admittance control strategy that allows to change online the interactive behavior while preserving a stable interaction with the environment. The effectiveness of the proposed architecture is experimentally validated.

Legibility can be defined as the ability of a robot to communicate its intent to the user. Legibility is relatively little investigated in multi-robot systems, but, in the literature, studies exist where the trajectory of manipulators is analyzed as a factor to improve the collaboration between robots and users. In this paper, we focus on the legibility of a group of mobile robots. To this end, we consider a set of motion-variables: trajectory, dispersion and stiffness. They are typical parameters that determine the motion of a group of robots. To analyze the effect of the motion-variables over legibility, Fisher's exact test and ANOVA (analysis of variance) were carried out. The data for the statistical analysis cover a full factorial plan and they were collected in a virtual reality set-up, where the users shared the environment with a group of robots. We investigate two aspects of legibility: the correctness and the rapidity of communication, namely if the communication happens correctly and how fast it happens. Trajectory was found to be relevant to correctly communicate the intention of the robots, while stiffness and dispersion were relevant for the rapidity of legibility.

The raise of collaborative robotics has allowed to create new spaces where robots and humans work in proximity. Consequently, to predict human movements and his/her final intention becomes crucial to anticipate robot next move, preserving safety and increasing efficiency. In this paper we propose a human-arm prediction algorithm that allows to infer if the human operator is moving towards the robot to intentionally interact with it. The human hand position is tracked by an RGB-D camera online. By combining the Minimum Jerk model with Semi-Adaptable Neural Networks we obtain a reliable prediction of the human hand trajectory and final target in a short amount of time. The proposed algorithm was tested in a multi-movements scenario with FANUC LR Mate 200iD/7L industrial robot.

The development of robotic systems with a certain level of autonomy to be used in critical scenarios, such as an operating room, necessarily requires a seamless integration of multiple state-of-the-art technologies. In this paper we propose a cognitive robotic architecture that is able to help an operator accomplish a specific task. The architecture integrates an action recognition module to understand the scene, a supervisory control to make decisions, and a model predictive control to plan collision-free trajectory for the robotic arm taking into account obstacles and model uncertainty. The proposed approach has been validated on a simplified scenario involving only a da VinciO surgical robot and a novel manipulator holding standard laparoscopic tools.

In this work we present a novel approach which compensates the destabilising effects of the time delay intrinsic in the control loop of an admittance-controlled robot employed for satellite dynamics simulation. The method is based on an energy storing element, the tank, which is exploited by the controller to preserve the passivity of the system and to avoid instability. Furthermore, we compare the performance of the proposed method with existing energy-based approaches, namely time-domain-passivity and wave variable transformation. The performance comparison and robustness of the methods are analysed in a Montecarlo simulation and validated experimentally.

The paper describes an estimation and identification procedure that allows to reconstruct the inertial parameters of a rigid load attached to the end-effector of an industrial manipulator. In particular, the proposed method adopts a multirate quaternion-based Kalman filter, fusing measurements obtained from robot kinematics and inertial sensors at possibly different sampling frequencies, to estimate linear accelerations and angular velocities/accelerations of the load. Then, a recursive total least-squares (RTLS) process is executed to identify the load parameters. Both steps of the estimation and identification procedure are performed in real-time, without the need for offline post-processing of measured data.

In order to make robot programming more easy and immediate, walk-through programming techniques can be exploited. However, a modification of a portion of the trajectory usually means to execute the path from the beginning. In this paper we propose a passivity-based framework to modify the trajectory online, manually driving the robot throughout the desired correction. The system follows the initial trajectory, encoded with Dynamical Movement Primitives, by setting high gains in the admittance control. When the human operator grabs the end-effector, the robot becomes compliant and the user can easily teach the desired correction, until he/she releases it at the end of the modification. Finally, the correction is optimally joined to the initial trajectory, restarting the path tracking. To avoid unsafe behaviors, the variation of the admittance parameters is performed exploiting energy tanks, in order to preserve the passivity of the interaction.

Accurate yield estimation is very important for improving the vineyard management, the quality of the grapes and the health of the vines. The most common systems use RGB image processing for achieving a good estimation. In order to collect images, robots or farming vehicles can be equipped with a RGB camera. In this paper, we propose a low-cost autonomous system which can navigate through a vineyard while collecting grape pictures in order to provide a yield estimation. Our system uses only a laser scanner to detect the row and follows it until its end, then it navigates towards the next one, exploiting the knowledge of the vineyard. The navigation algorithm was tested both in simulation and in a real environment with good results. Furthermore, a yield estimation of two different grape varieties is presented.

In this paper we consider a multi-robot system that shares the environment with external entities, and we propose a methodology for controlling the interaction with them. In particular, we consider the problem of achieving a desired dynamic interaction model, in such a way that the multi-robot system exchanges desired forces with external entities. This is obtained by introducing local deformations of the coupling actions among the robots. The proposed method ensures preservation of the passivity property, which provides safety guarantees in the interaction with the (possibly poorly known) external entities.

In this paper we address the problem of controlling a robotic system mounted on an actuated floating base for space applications. In particular, we investigate the stability issues due to the low rate of the base control unit. We propose a passivity-based stabilizing controller based on the time domain passivity approach. The controller uses a variable damper regulated by a designed energy observer. The effectiveness of the proposed strategy is validated on a base-manipulator multibody simulation.

In multi-robot systems passive interconnections among agents are often exploited to achieve a desired and robustly stable cooperative behavior. Nevertheless, the passivity constraint limits the kinds of behaviors that can be achieved. In this paper, we exploit the concept of energy tank for building a novel generalized interconnection that allows to impose any kind of dynamic coupling between two passive systems in a flexible way while preserving the passivity of the overall coupled system. The proposed strategy is validated by simulations and experiments.

In this paper we present a general framework for affective human-robot interaction that allows users to intuitively interact with a robot and takes into account their mental fatigue, thus simplifying the task or providing assistance when the user feels stressed. Interaction with the robot is achieved by naturally mapping user's forearm motion, detected with a smartwatch, into robot's motion. High-level commands can be provided by means of gestures. An approach based on affective robotics is used to adapt the level of robot's autonomy to the cognitive workload of the user. User's mental fatigue is detected from the analysis of heart rate, also measured by the smartwatch. The framework is general and can be applied to different robotic systems. In this paper, we consider its experimental validation on a wheeled mobile robot.

In physical human-robot interaction, the coexistence of robots and humans in the same workspace requires the guarantee of a stable interaction, trying to minimize the effort for the operator. To this aim, the admittance control is widely used and the appropriate selection of the its parameters is crucial, since they affect both the stability and the ability of the robot to interact with the user. In this paper, we present a strategy for detecting deviations from the nominal behavior of an admittance-controlled robot and for adapting the parameters of the controller while guaranteeing the passivity. The proposed methodology is validated on a KUKA LWR 4+.

This paper presents TIREBOT, a novel tire-workshop robotic co-worker that can safely move in a tire workshop and assist the operator in lifting and transporting wheels among several working stations. A safe and cooperative navigation strategy based on the concept of danger field is illustrated. Finally, TIREBOT is experimentally evaluated in a real tire-workshop and used by real operator in order to assess the usability and the effectiveness of the robot in a real operating scenario.

In this paper we consider the problem of controlling the dynamic behavior of a multi-robot system while interacting with the environment. In particular, we propose a general methodology that, by means of locally scaling inter-robot coupling relationships, leads to achieving a desired interactive behavior. The proposed method is shown to guarantee passivity preservation, which ensures a safe interaction. The performance of the proposed methodology is evaluated in simulation, over large-scale multi-robot systems.

In this paper we present a passive and reliable explicit discrete integrator, which allows to preserve the energy and dynamic properties of a physical body rendered on a hardware-in-the-loop simulator. Starting from the standard Euler integrator, we identify the energy generation that results from the integration process. This energy makes the time discrete dynamics deviate from the ideal one, resulting in position drifts or stability issues. By exploiting the time domain passivity approach, the simulated dynamics is reshaped in order to preserve its physical energy properties. The proposed integration method allows precise simulation of virtual bodies on industrial robot facilities. The method has been validated in simulation and experimentally tested on the DLR OOS-SIM facility.

Teleoperating a quadrotor equipped with a monocular camera for exploring a wide area in search of something has become a common practice in many application scenarios (e.g. search and rescue). In order to efficiently plan operations, estimating the 3D pose of a point of interest is as important as detecting it. In this paper we propose a novel bilateral teleoperation architecture where an estimation scheme is exploited for recovering the position of a set of visual features while an operator steers the motion of the quadrotor UAV. The operator acts on a force-feedback master device that produces force cues meant to suggest where to drive the quadrotor for improving the convergence rate of the estimation process. The effectiveness of the proposed teleoperation strategy is validated by means of hardware in the loop simulations.

Admittance control is a widely used approach for guaranteeing a compliant behavior of the robot in physical human-robot interaction. When an admittance-controlled robot is coupled with a human, the dynamics of the human can cause deviations from the desired behavior of the robot, mainly due to a stiffening of the human arm, and thus generate high-frequency unsafe oscillations of the robot. In this paper we present a novel methodology for detecting the rising oscillations in the human-robot interaction. Furthermore, we propose a passivity-preserving strategy to adapt the parameter of the admittance control in order to get rid of the high-frequency oscillations and, when possible, to restore the desired interaction model. A thorough experimental validation of the proposed strategy is performed on a group of 26 users performing a cooperative task.

In this paper we address the problem of assigning a set of tasks to a set of Automated Guided Vehicles (AGVs), in a conflict-free manner. Specifically, we consider a system of multiple AGVs, moving along a predefined roadmap, and utilized for transportation of goods in automated warehouses. Sequential application of task assignment and path planning often gives rise to pathological situations, such as deadlocks, in which AGVs block each other, thus preventing tasks completion. In this paper we propose a method for assigning tasks while taking into account the subsequent path planning, encoding possible conflicts into a conflict graph, that is subsequently utilized for defining constraints of an optimization problem. Simulations are performed on maps of real industrial environments, to compare the proposed method with traditional task assignment.

This paper proposes a passive and explicit integrator for simulating a rotational rigid-body dynamics rendered by a robot. Considering the Euler integration method, active energy terms are identified. These sources of energy are due to the external torque and the coupled dynamics which can lead to a non-physical behavior of the simulated dynamics. The proposed method dissipates this energy using a variable damper regulated by an energy observer. The new algorithm guarantees not only passivity but also a consistent energetic integration. The integration method is sustained by simulations and tested on a real-time hardware-in-the-loop simulator.

In this paper, we propose a novel methodology for achieving complex dynamic behaviors in multirobot systems. In particular, we consider a multirobot system partitioned into two subgroups: 1) dependent and 2) independent robots. Independent robots are utilized as a control input, and their motion is controlled in such a way that the dependent robots solve a tracking problem, that is following arbitrarily defined setpoint trajectories, in a coordinated manner. The control strategy proposed in this paper explicitly addresses the collision avoidance problem, utilizing a null space-based behavioral approach: this leads to combining, in a non conflicting manner, the tracking control law with a collision avoidance strategy. The combination of these control actions allows the robots to execute their task in a safe way. Avoidance of collisions is formally proven in this paper, and the proposed methodology is validated by means of simulations and experiments on real robots.

This paper introduces a control strategy for obtaining cooperative tracking of periodic setpoint trajectories in multi-robot systems. A heterogeneous group of robots is considered: a few independent robots are used as a control input for the system, with the aim of controlling the position of the remaining robots, namely the dependent ones. The control strategy presented in this paper explicitly considers changes in the communication topology among the robots. These changes happen as the system evolves, since robots are equipped with finite range communication devices.

Wave variables are a very popular approach for dealing with communication delay in bilateral teleoperation because of their effectiveness and of their simplicity. Nevertheless, the inherent dynamics of wave based communication channels is often deleterious for the transparency of the teleoperation system. Recently proposed architectures like TDPN, PSPM and two layers approach allow to achieve a high transparency at the price of a complex architecture, with some parameters to tune empirically. In this paper we propose a novel wave based architecture that blends the high performance that can be achieved by recently proposed architectures with the simplicity of wave based bilateral teleoperation.

This paper describes a walk-through programming technique, based on admittance control and tool dynamics compensation, to ease and simplify the process of trajectory learning in common industrial setups. In the walk-through programming, the human operator grabs the tool attached at the robot end-effector and “walks” the robot through the desired positions. During the teaching phase, the robot records the positions and then it will be able to interpolate them to reproduce the trajectory back. In the proposed control architecture, the admittance control allows to provide a compliant behavior during the interaction between the human operator and the robot end-effector, while the algorithm of compensation of the tool dynamics allows to directly use the real tool in the teaching phase. In this way, the setup used for the teaching can directly be the one used for performing the reproduction task. Experiments have been performed to validate the proposed control architecture and a pick and place example has been implemented to show a possible application in the industrial field.

Because of their simplicity, wave variables have become almost a standard strategy for stabilizing delayed bilateral teleoperation systems. However, the price to pay for a stable behavior is a degradation in the performance of the teleoperation system. Recently, more flexible and transparency oriented bilateral architectures have been proposed (e.g. TDPN, PSPM, Two-Layer approach) but they are complex to implement and to tune. In [1], a strategy for blending the high performance of the new control methodologies with the simplicity of wave based bilateral teleoperation has been proposed. Nevertheless, while appealing in terms of simplicity, this method is conservative in terms of the transparency that can be achieved. In this paper, we extend the architecture in [1] in order to optimize the use of the energy and for achieving a coupling that is as close as possible to the desired one while preserving the passivity of the overall system.

In this paper we consider the problem of coordinating the motion of a group of Automated Guided Vehicles (AGVs) utilized in industrial environments for logistics operations. In particular, we consider a hierarchical coordination strategy, where the environment is partitioned into sectors: coordination on the top layer defines the sequence of sectors to be traveled, while coordination on the bottom layer deals with traffic management inside each sector. In this paper we introduce a novel partitioning algorithm, that defines the sectors in a dynamic manner, taking into account both the shape of the (generally non-convex) environment, and the current distribution of the AGVs. This is achieved exploiting a clustering algorithm, and subsequently defining the sectors based on the geodesic distance.

This paper introduces a performance oriented method for simulating stable free-floating satellite dynamics on a position controlled robot. Intrinsic latencies found in robot controllers, i.e. between input and output data, are known to produce stability issues and performance degradation. These issues are even more apparent during contact phases, where impact dynamics play a major role. The approach presented in this paper guarantees stability through passivity and preserves the performance through the use of an optimal damping. The energy produced by delays found in the closed loop system is monitored and dissipated when necessary. In order to implement the dynamics accurately, the damping process is formulated as an optimization problem. Thus, over-dissipation can be avoided and the system becomes less conservative. Performance and effectiveness of the method are shown in simulation and verified experimentally on a position controlled seven degrees of freedom Light Weight Robot equipped with a force-torque sensor at the end-effector.

This paper describes innovative sensing technologies and control techniques, that aim at improving the performance of groups of Automated Guided Vehicles (AGVs) used for logistics operations in industrial environments. We explicitly consider the situation where the environment is shared among AGVs, manually driven vehicles, and human operators. In this situation, safety is a major issue, that needs always to be guaranteed, while still maximizing the efficiency of the system. This paper describes some of the main achievements of the PAN-Robots European project.

In this paper we propose a novel algorithm for the dynamic routing of a group of Autonomous Guided Vehicles (AGVs) used for transporting goods in automatic warehouses. Our strategy allows to improve the efficiency of a fleet of AGVs in terms of delivery time and its computational burden is sufficiently small to be embedded in standard industrial traffic management system. The algorithm is validated in a small-scale automatic warehouse with real AGVs.

In this paper we introduce the design of a light-weight novel flexible-joint arm for light-weight unmanned aerial vehicles (UAVs), which can be used both for safe physical interaction with the environment and it represents also a preliminary step in the direction of performing quick motions for tasks such as hammering or throwing. The actuator consists of an active pulley driven by a rotational servo motor, a passive pulley which is attached to a rigid link, and the elastic connections (springs) between these two pulleys. We identify the physical parameters of the system, and use an optimal control strategy to maximize its velocity by taking advantage of elastic components. The prototype can be extended to a light-weight variable stiffness actuator. The flexible-joint arm is applied on a quadrotor, to be used in aerial physical interaction tasks, which implies that the elastic components can also be used for stable interaction absorbing the interactive disturbances which might damage the flying system and its hardware. The design is validated through several experiments, and future developments are discussed in the paper.

Autonomous vehicles require advances sensing technologies, in order to be able to safely share the environment with human operators. Those sensing technologies are in fact necessary for identifying the presence of unforeseen objects, and measuring their position and velocity. Furthermore, classification is necessary for effectively predicting their behavior. In this paper we consider the presence of sensing systems both on-board each vehicle, and installed on infrastructural elements. While the simultaneous presence of multiple sources of information heavily improves the amount (and quality) of available data, it generates the need for effective data fusion and storage systems. Hence, we introduce a centralized cloud service, that is in charge of receiving and merging data acquired by different sensing systems. Those data are then distributed to the autonomous vehicles, that exploit them for implementing advanced navigation strategies. The proposed methodology is validated in a real industrial environment to safely perform obstacle avoidance with an autonomously driven forklift.

The paper describes a passivity based approach to the generation of virtual fixtures for robotic teleoperation schemes involving multiple masters and multiple slaves. Virtual fixtures considered in the paper aim to guide the user towards a geometric path, which is assumed to be collision-free by design, describing a desired execution of a given task. To preserve safe distance from obstacles and at the same time suggest the user a preferred direction to progress along the path, the virtual fixtures are generated by arbitrarily redirecting assistive forces obtained by summation of attractive and repulsive potential fields. The main result of the paper is the definition of a passivity preserving condition for this redirection, so that the behavior of the teleoperated systems remains safe and stable. The proposed assisted mode of teleoperation has been tested on a surgical robot prototype with dual arms configuration, since robotic surgery represents a suitable application domain for such control schemes.

When teleoperating a multi-robot system it is useful to control the kind of behavior of the fleet depending on the environment it is moving in. In this paper, a novel bilateral control architecture for teleoperating a group of mobile robots is proposed. The user can command the robots both as a flexible and amorphous group and as a set of agents executing different trajectories for achieving a desired task, mimicking a conductor-orchestra paradigm. Exploiting passivity based control, we ensure a stable and safe behavior for the user. The proposed teleoperation strategy is validated by means of experiments.

This paper deals with a holistic approach to coordinate a fleet of automated guided vehicles (AGVs) in an industrial environment. We propose an ensemble approach based on a two layer control architecture and on an automatic algorithm for the definition of the roadmap. The roadmap is built by considering the path planning algorithm implemented on the hierarchical architecture and vice versa. In this way, we want to manage the coordination of the whole system in order to increase the flexibility and the global efficiency. Furthermore, the roadmap is computed in order to maximize the redundancy, the coverage and the connectivity. The architecture is composed of two layers. The low-level represents the roadmap itself. The high-level describes the topological relationship among different areas of the environment. The path planning algorithm works on both these levels and the subsequent coordination among AGVs is obtained exploiting shared resource (i.e., centralized information) and local negotiation (i.e., decentralized coordination). The proposed approach is validated by means of simulations and comparison using real plants. Note to Practitioners-The motivation of this work grows from the need to increase the flexibility and efficiency of current multi-AGV systems. In particular, in the current state-of-the-art the AGVs are guided through a manually defined roadmap with ad-hoc strategies for coordination. This is translated into high setup time requested for installation and the impossibility to easily respond to dynamic changes of the environment. The proposed method aims at managing all the design, setup and control process in an automatic manner, decreasing the time for setup and installation. The flexibility is also increased by considering a coordination strategy for the fleet of AGVs not based on manual ad-hoc rules. Simulations are performed in order to compare the proposed approach to the current industrial one. In the future, industrial aspects, as the warehouse management system, will be integrated in order to achieve a real and complete industrial functionality.

In order to accomplish cooperative tasks, decentralized systems are required to communicate among each other. Thus, maintaining the connectivity of the communication graph is a fundamental issue. Connectivity maintenance has been extensively studied in the last few years, but generally considering undirected communication graphs. In this paper, we introduce a decentralized control and estimation strategy to maintain the strong connectivity property of directed communication graphs. In particular, we introduce a hierarchical estimation procedure that implements power iteration in a decentralized manner, exploiting an algorithm for balancing strongly connected directed graphs. The output of the estimation system is then utilized for guaranteeing preservation of the strong connectivity property. The control strategy is validated by means of analytical proofs and simulation results.

Introducing some form of autonomy in robotic surgery is being considered by the medical community to better exploit the potential of robots in the operating room. However, significant technological steps have to occur before even the smallest autonomous task is ready to be presented to the regulatory authorities. In this paper, we address the initial steps of this process, in particular the development of control concepts satisfying the basic safety requirements of robotic surgery, i.e., providing the robot with the necessary dexterity and a stable and smooth behavior of the surgical tool. Two specific situations are considered: the automatic adaptation to changing tissue stiffness and the transition from autonomous to teleoperated mode. These situations replicate real-life cases when the surgeon adapts the stiffness of her/his arm to penetrate tissues of different consistency and when, due to an unexpected event, the surgeon has to take over the control of the surgical robot. To address the first case, we propose a passivity-based interactive control architecture that allows us to implement stable time-varying interactive behaviors. For the second case, we present a two-layered bilateral control architecture that ensures a stable behavior during the transition between autonomy and teleoperation and, after the switch, limits the effect of initial mismatch between master and slave poses. The proposed solutions are validated in the realistic surgical scenario developed within the EU-funded I-SUR project, using a surgical robot prototype specifically designed for the autonomous execution of surgical tasks like the insertion of needles into the human body.

Decentralized control strategies for multirobot systems have been extensively studied over the past few years. Typically, these strategies aim at exploiting local interaction rules to regulate the overall state of the multirobot system toward a desired configuration, thus generating some desired coordinated behaviors, such as synchronization, swarming, deployment, or formation control. However, when considering the real-world application of multirobot systems, more complex cooperative dynamic behaviors are desirable. Along these lines, in this paper, we propose a methodology to control a multirobot system for cooperatively tracking arbitrarily defined periodic setpoint trajectories. This objective is fulfilled partitioning the multirobot system into independent robots (that can provide control inputs) and dependent robots (that are controlled through local interaction). The motion of the independent robots is then defined in such a way that, exploiting local interactions, the dependent robots are controlled to track the desired trajectories. The proposed control strategy is validated by means of simulations and experiments on real robots.

This paper deals with decentralized coordination of Automated Guided Vehicles (AGVs). We propose a hierarchical traffic control algorithm, that implements path planning on a two layer architecture. The high-level layer describes the topological relationships among different areas of the environment. In the low-level layer, each area includes a set of fixed routes, along which the AGVs have to move. An algorithm is also introduced for the automatic definition of the route map itself. The coordination among the AGVs is obtained exploiting shared resources (i.e. centralized information) and local negotiation (i.e. decentralized coordination). The proposed strategy is validated by means of simulations using real plant.

Decentralized control of networked systems has been widely investigated in the literature, with the aim of regulating the overall state of the system to some desired configuration, thus obtaining coordinated emerging behaviors (e.g. synchronization, swarming, coverage, formation control) by means of local interaction. In this paper we introduce a methodology to solve a tracking problem, that is defining a decentralized control strategy for making a networked system follow an arbitrarily defined periodic setpoint function. The most suitable interconnection topology is defined together with the control law as the solution of a constrained optimization problem, in order to ensure asymptotic tracking. Simulations are provided for validating the proposed control strategy.

In this paper we propose a controller, based on an extension of Interconnection and Damping Assignment-Passivity Based Control (IDA-PBC) framework, for shaping the whole physical characteristics of a quadrotor and for obtaining a desired interactive behavior between the robot and the environment. In the control design, we shape the total energy (kinetic and potential) of the undamped original system by first excluding external effects. In this way we can assign a new dynamics to the system. Then we apply damping injection to the new system for achieving a desired damped behavior. Then we show how to connect a high-level control input to such system by taking advantage of the new desired physics. We support the theory with extensive simulations by changing the overall behavior of the UAV for different desired dynamics, and show the advantage of this method for sliding on a surface tasks, such as ceiling painting, cleaning or surface inspection.

This paper deals with the automatic generation of a roadmap. We propose an approach to build a roadmap for Automated Guided Vehicles (AGVs) used for logistics operations in industrial environments. The algorithm computes a roadmap in such a way that the coverage, the connectivity and the redundancy of the paths are maximized. In this way the flexibility and the efficiency of the AGV system can be increased. The proposed approach is validated by means of comparison with different roadmaps manually built in real plants.

Networked systems and decentralized control strategies have been widely investigated in the literature, with the objective of obtaining coordinated emerging behaviors by means of local interaction. While typical approaches aim at solving regulation problems (e.g. synchronization, swarming, coverage, formation control) a few works have recently appeared that move towards the solution of more complex problems, such as tracking of arbitrary setpoint functions. Based on the formulation introduced in [1], this objective is obtained in this paper partitioning the networked systems into leaders (that can provide control inputs) and followers (that are controlled through local interaction). In this paper we provide a methodology for letting the leaders estimate the state of the followers in a decentralized manner: this estimate is then used for control purposes. Simulations are provided for validating the proposed control strategy.

The paper describes a software architecture for control and simulation of a generic robotic manipulator. The algorithmic part of the system is implemented using the Orocos component-based framework and its related library for robotic applications, while the graphical animation of the robot is developed with Blender. The proposed control and simulation framework is modular, reconfigurable and computationally efficient. Moreover, it can be seamlessly integrated into a more complex control architecture for a complete intelligent robotic system.

In this paper, we present a new impedance control strategy that allows to reproduce a time-varying stiffness. By properly controlling the energy exchanged during the action, we guarantee the system passivity for any choice of the stiffness matrix, especially in case of time-varying stiffness, and therefore a stable behavior of the robot both in free motion and in interaction with an environment.

In this paper we introduce a collision avoidance control strategy for groups of mobile robots moving in a three-dimensional environment, whose dynamics are described according to the Lagrangian model. The proposed strategy is based on the use of gyroscopic forces, that ensure obstacle avoidance without interfering with the convergence properties of the multi-robot system's desired control law. Moreover, we introduce a method to define the direction of the force in an optimal way, in order to introduce the smallest possible perturbation with respect to the desired behavior of the system. Collision avoidance and convergence properties are analytically demonstrated, and simulation results are provided for validation purpose.

This paper presents a novel bilateral controller that allows to stably teleoperate the degree of connectivity in the mutual interaction between a remote group of mobile robots considered as the slave-side. A distributed leader-follower scheme allows the human operator to command the overall group motion. The group autonomously maintains the connectivity of the interaction graph by using a decentralized gradient descent approach applied to the Fiedler eigenvalue of a properly weighted Laplacian matrix. The degree of connectivity, and then the flexibility, of the interaction graph can be finely tuned by the human operator through an additional bilateral teleoperation channel. Passivity of the overall system is theoretically proven and extensive human/hardware in-the-loop simulations are presented to empirically validate the theoretical analysis.

Decentralized control of networked systems has been widely investigated in the literature, with the aim of obtaining coordinated emerging behaviors (e.g. synchronization, swarming, coverage, formation control) by means of local interaction. In this paper we consider the possibility of injecting external inputs into the networked system, in order to obtain more complex cooperative behaviors. Specifically, we introduce a strategy that makes it possible to control the overall state of the networked system by directly controlling only a subset of the networked agents, namely the leaders. Exploiting local interaction rules, it is possible to define the inputs for the leaders in such a way that each follower is forced to track a desired periodic setpoint.

This study introduces a control algorithm that, exploiting a completely decentralized estimation strategy for the algebraic connectivity of the graph, ensures the connectivity maintenance property for multi robot systems, in the presence of a generic (bounded) additional control term. This result is obtained by driving the robots along the negative gradient of an appropriately defined function of the algebraic connectivity. The proposed strategy is then enhanced with the introduction of the concept of critical robots, that is robots for which the loss of a single communication link might cause the disconnection of the communication graph. Limiting the control action to critical robots will be shown to reduce the control effort that is introduced by the proposed connectivity maintenance control law and to mitigate its effect on the additional (desired) control term.

While RGB-D sensors are becoming more and more popular in mobile robotics laboratories, they are usually not yet adopted for industrial applications. In fact, in this field, depth measurements are generally acquired by means of laser scanners and, when visual information is needed, by means of stereo-cameras. The aim of this paper is to perform an experimental validation, to compare the performance of a stereo-camera and an RGB-D sensor, in a specific application: mobile robot localization for industrial applications. Experiments are performed exploiting artificial landmarks (defined by a self-similar pattern), placed in known positions in the environment.

In order to accomplish cooperative tasks, multi-robot systems are required to communicate among each other. Thus, maintaining the connectivity of the communication graph is a fundamental issue. Connectivity maintenance has been extensively studied in the last few years, but generally considering only kinematic agents. In this paper we will introduce a control strategy that, exploiting a decentralized procedure for the estimation of the algebraic connectivity of the graph, ensures the connectivity maintenance for groups of Lagrangian systems. The control strategy is validated by means of analytical proofs and simulation results.

In this paper, we present a passivity-based decentralized approach for bilaterally teleoperating a group of UAVs composing the slave side of the teleoperation system. In particular, we explicitly consider the presence of time delays, both among the master and slave, and within UAVs composing the group. Our focus is on analyzing suitable (passive) strategies that allow a stable teloperation of the group despite presence of delays, while still ensuring high flexibility to the group topology (e.g., possibility to autonomously split or join during the motion). The performance and soundness of the approach is validated by means of human/hardware-in-the-loop simulations (HHIL).

In this paper, a novel decentralized control strategy for bilaterally teleoperating heterogeneous groups of mobile robots from different domains (aerial, ground, marine, and underwater) is proposed. By using a decentralized control architecture, the group of robots, which is treated as the slave side, is made able to navigate in a cluttered environment while avoiding obstacles, interrobot collisions, and following the human motion commands. Simultaneously, the human operator acting on the master side is provided with a suitable force feedback informative of the group response and of the interaction with the surrounding environment. Using passivity-based techniques, we allow the behavior of the group to be as flexible as possible with arbitrary split and join events (e.g., due to interrobot visibility/packet losses or specific task requirements) while guaranteeing the stability of the system. We provide a rigorous analysis of the system stability and steady-state characteristics and validate performance through human/hardware-in-the-loop simulations by considering a heterogeneous fleet of unmanned aerial vehicles (UAVs) and unmanned ground vehicles as a case study. Finally, we also provide an experimental validation with four quadrotor UAVs.

Telerobotics is one of the most traditional fields of robotics and it played a crucial role in the history of robotics and of the mankind, especially in the areas of space and undersea exploration and of remote material handling. On the other hand, teleoperation is still a very active research area and many problems are still open. In particular, the design of the control strategy for coupling local and remote site is of paramount importance for implementing telepresence, namely the feeling of being directly interacting with the remote environment. The IEEE RAS Technical Committee on Telerobotics would like to propose a half-day tutorial for illustrating several successful control strategies for implementing high performance bilateral teleoperation systems.

In this paper, a novel distributed control strategy for teleoperating a fleet of Unmanned Aerial Vehicles (UAVs) is proposed. Using passivity based techniques, we allow the behavior of the UAVs to be as flexible as possible with arbitrary split and join decisions while guaranteeing stability of the system. Furthermore, the overall teleoperation system is also made passive and, therefore, characterized by a stable behavior both in free motion and when interacting with unknown passive obstacles. The performance of the system is validated through semi-experiments.

In this paper we consider the global localization problem for an industrial AGV moving in a known environment. The problem consists of determining the pose of the vehicle without any prior information about its location. The vehicle is supposed to be equipped with a laser scanner that allows to measure the range and bearing of the vehicle with respect to a set of anonymous landmarks. A map with the positions of all landmarks in the environment is available to the localization system. We propose a novel algorithm for AGV self-localization based on landmarks identification that can take into account also false detections, very common in industrial environments. The pose is computed with a single scan (2D), without any sensor fusion. The performance of the proposed strategy is shown both by simulations and experiments on real industrial plants.

In this paper, we present an experimental validation of a novel decentralized passivity-based control strategy for teleoperating a group of Unmanned Aerial Vehicles (UAVs): the slave side, consisting of the UAVs, is endowed with large group autonomy by allowing time-varying topology and interrobot/obstacle collision avoidance. The master side, represented by a human operator, controls the group motion and receives suitable force feedback cues informing her/him about the remote slave motion status. Passivity theory is exploited for guaranteeing stability of the slave side and of the overall teleoperation channel. Results of experiments involving the use of 4 quadcopters are reported and discussed, confirming the soundness of the paper theoretical claims.

In this paper we propose an algorithm for coordinating a fleet of Automated Guided Vehicles (AGVs) that go through predefined paths in a dynamic industrial environment. Coordination diagrams are used to define a mapping between the configuration space of the fleet and a set of motion constraints that the vehicles must satisfy in order to avoid mutual collisions. The motion actions that maximize the advancement of the fleet while respecting the constraints are determined by a polynomial time heuristic algorithm.

In this paper we present a decentralized control strategy for the connectivity maintenance for groups of mobile robots performing some desired task. Exploiting a completely decentralized estimation strategy for the algebraic connectivity of the graph, we prove the connectivity maintenance property in the general case, i.e. in presence of a generic (bounded) additional control term. Then, we address two specific decentralized control applications: rendezvous and formation control. We analytically prove that our control strategy ensures the global connectivity maintenance, while preserving the convergence properties of the rendezvous and formation controllers respectively. Simulations and experimental results are presented as well, in order to show the effectiveness of the proposed control law.

In this paper, a two-layer approach is presented to guarantee the stable behavior of bilateral telemanipulation systems in the presence of time-varying destabilizing factors such as hard contacts, relaxed user grasps, stiff control settings, and/or communication delays. The approach splits the control architecture into two separate layers. The hierarchical top layer is used to implement a strategy that addresses the desired transparency, and the lower layer ensures that no “virtual” energy is generated. This means that any bilateral controller can be implemented in a passive manner. Separate communication channels connect the layers at the slave and master sides so that information related to exchanged energy is completely separated from information about the desired behavior. Furthermore, the proposed implementation does not depend on any type of assumption about the time delay in the communication channel. By complete separation of the properties of passivity and transparency, each layer can accommodate any number of different implementations that allow for almost independent optimization. Experimental results are presented, which highlight the benefit of the proposed framework.

The paper presents a nonlinear filtering technique that can be adopted to generate smooth trajectories for mobile robotic applications. The proposed trajectory planner can be fully executed online by the robot control system, thanks to its inherently discrete-time behavior and to its limited computational requirement. The outputs of the nonlinear filter used as a trajectory planner include the derivatives of the desired position in the cartesian plane up to the third order. This allows the implementation of feedback linearization control schemes that can transform the dynamics of a mobile robot in a double chain of three integrators, exploiting the highest derivative of the filter's output as a feedforward action. Finally, the paper reports experimental results obtained by the full implementation of the proposed trajectory planning and control scheme on a real unicycle-like robot.

In this paper we address the trajectory tracking problem for groups of mobile robots. We consider trajectories described by completely arbitrary shaped closed curves. The proposed control strategy is a completely decentralized algorithm, and does not require any global synchronization. The desired behavior is obtained by means of some properly designed artificial potential functions.

In this paper a force scaling function for an haptic system is the output of the psychophysics experiments that have been carried out with the aim of better understanding the human perception capabilities. The experimental work consists in measuring the differential thresholds of force perception applied to the hand-arm system. These findings support our claim that the human perception of forces and torques depends on force intensity and works differently along different directions, thus suggesting that perception can be enhanced by suitable scaling. We have identified a scaling function for each direction and we have shown that this variable scalings can be safely embedded in a passivity based teleoperation system in order to improve the feeling perceived by the user during the interaction with remote environments.

In this paper we describe a novel decentralized control strategy to realize formations of mobile robots. We first describe a methodology to obtain a formation with the shape of a regular polygon. Then, applying a bijective coordinates transformation, we show how to obtain a formation with an arbitrary shape. Our control strategy is based on the interaction of some artificial potential fields, but it is not affected by the problem of local minima.

In this paper we propose a methodology for coordinating a group of mobile robots following predefined paths in a dynamic industrial environment. Coordination diagrams are used for representing the possible collisions among the robots. Exploiting the structure of the industrial application we are dealing with, we propose an algorithm for efficiently composing the coordination diagram. Furthermore, we classify the possible collisions that can take place and the induced geometry of the resulting coordination diagram. Finally, we exploit this information for developing a planning algorithm that allows to coordinate the robots and to take into account unexpected events that can occur in an industrial environment.

In this paper we address the problem of formation control of a group of robots that exchange information over a delayed communication network. We consider the Virtual Body Artificial Potential approach for stabilizing a group of robots at a desired formation. We show that it is possible to model the controlled system as a set of elements exchanging energy along a power preserving interconnection structure. We exploit the scattering framework to stabilize the robots in the desired formation independently of any delay in the communication of the information.

After stability, transparency is the major issue in the design of a telemanipulation system. In this paper, we exploit the behavioral approach in order to provide an index for the evaluation of transparency in port-Hamiltonian-based teleoperators. Furthermore, we provide a transparency analysis of packet switching scattering-based communication channels.

This paper describes a modeling language that aims to provide a unified framework for representing control systems, namely, physical plants coupled with computer-based control devices. The proposed modeling methodology is based on the cardinal principle of object orientation, which allows describing both control software and physical components using the same basic concepts, particularly those of capsules, ports, and protocols. Furthermore, it is illustrated how the well-known object-oriented specification language unified modeling language can be adopted, provided an adequate formalization of its semantics, to describe structural and behavioral aspects of control systems, related to both logical and physical parts. Note to Practitioners-The development of an automated system within an industrial setting is a complex task, whose successful result depends on the joint efforts of a team of designers with different scientific backgrounds and specialized knowledge. In fact, an automated system is typically composed of a mechanical assembly, which must be precisely designed and manufactured, and a set of sensors and actuators (e.g., electrical drives, pneumatic systems, etc.), which are, on their turn, controlled most of the time by means of digital processors. Of course, both electrical parts and control algorithms (e.g., proportional, integral, and derivative (PID) regulators, logic and supervisory control, reference trajectories for mechanical motions, etc.) should be designed with the same care given to mechanical aspects. Moreover, it is undeniable that none of the various parts composing the automated system design specification can, on their own, allow engineers to understand the actual behavior of the whole system, especially without a common description language that is understandable for all of the designers. The present paper introduces a unified language which aims to support integrated design specifications of automated systems, including the dynamics of heterogeneous physical assemblies, the discrete-event behavior of distributed control software, and the specification of interface ports between the plant and the control system. With the proposed language, it is possible to obtain a complete picture of the automated system suitable for its simulation, documentation, and validation. The modeling language described in the paper supports the principles of object orientation. This choice moves in the direction of enhancing modularity and reusability properties of design specifications, which are aspects of great importance in the design practice. Moreover, the object-oriented approach to automated systems design proposed in the paper aims to introduce the concept of "design by extension" in the manufacturing industry. This means that the definition of specialization relationships between classes of components implies that those components should be designed in order to be substitutable with each other, especially from a dynamic point of view. This aspect will be the subject of further papers illustrating other practical insights on the use of object-oriented models for automated systems

In several applications involving haptic interfaces it can be desirable to scale the interaction force perceived by the user. The most intuitive approach is to change the stiffness of the virtual environment but, unfortunately, changing the physical parameters that characterize a virtual environment is a potentially destabilizing action. In this paper we embed in the intrinsically passive haptic scheme recently proposed in S. Stramigioli et al. (2005) a power scaling interconnection that allows to scale the force perceived by the user while preserving the passivity, and consequently the stable behavior, of the overall system

Passivity based bilateral telemanipulation schemes are often subject to a position drift between master and slave if the communication channel is implemented using scattering variables. The magnitude of this position mismatch can be significant during interaction tasks. In this paper we propose a passivity preserving scheme for compensating the position drift arising during contact tasks in port-Hamiltonian based telemanipulation improving the kinematic perception of the remote environment felt by the human operator

The aim of the paper is to provide a practical method to introduce design principles typical of the object-oriented approach, like “design by extension”, to the application domain of manufacturing systems control design. The proposed method is based on a domain-specific extension of the modeling language UML and on the formalization of design models as transition systems for verification purposes. Object-oriented models, formalized according to the proposed semantics, can be analyzed with model checking techniques in order to verify the behavioral conformity of object classes, according to a notion of substitutability which is defined in the paper specifically for the proposed modeling language.

The aim of this paper is to provide a unified language for modeling both control software and physical plants in real time control systems. This is done by embedding the bond graph modeling language for physical systems into the UML-RT framework, widely used to model distributed real-time software.

After stability, transparency is the major issue in the design of a telemanipulation system. In this paper we exploit a behavioral approach in order to provide an index for the evaluation of transparency in port-Hamiltonian based teleoperators. Furthermore we provide a transparency analysis of packet switching scattering based communication channels.

In several applications involving bilateral telemanipulation, master and slave robots act at different power scales (e.g. telesurgery). The aim of this paper is to embed power scaling into port-Hamiltonian based bilateral telemanipulation schemes, In order to deal with nonnegligible transmission delays we propose a novel scattering based communication strategy to properly scale the power exchanged by master and slave while preserving a stable behavior of the overall scheme.

In this paper, we present a novel way to approach the interconnection of a continuous and a discrete time physical system first presented in . This is done in a way which preserves passivity of the coupled system independently of the sampling time T. This strategy can be used both in the field of telemanipulation, for the implementation of a passive master/slave system on a digital transmission line with varying time delays and possible loss of packets (e.g., the Internet), and in the field of haptics, where the virtual environment should 'feel' like a physical equivalent system.

In this paper we present an intrinsically passive telemanipulation scheme over a digital transmission line Internet-like. We present an analysis of the energetic behavior of the communication line both in case of loss of packages and in case of variable delay. The sample data nature of the passive controller is explicitly taken into account following the approach outlined.

In this paper two problems arising in the digital passive scheme for telemanipulation presented in are addressed. At first, we show how to preserve system passivity in presence of quantization error introduced by position sensor (i.e. encoders) by introducing energy dissipation. Then, we introduce a scheme for a redundant communication channel that will compensate for missed packets improving performances while preserving passivity of the overall scheme.

In this paper the problem of delayed virtual environments in haptics is addressed. We show that the approach outlined is no longer passive in case of (computational) delay on the output of the virtual environment. Passivity can be recovered using scattering theory; a discretization algorithm which leads to a discrete passive port-Hamiltonian systems with respect to any delay on the output is proposed.

This paper presents a novel approach to the interconnection of a continuous time and a discrete time physical system. This is done in a way which preserves the passivity of the coupled system independently of the sampling time. A direct application in the field of haptic displays, where a virtual environment should feel like equivalent physical systems, is presented.

In this paper, an extension of the so-called intrinsic passive control (IPC) is illustrated, showing that an improvement of performances can be achieved by considering different types of energy-storing elements, i.e. "springs", in the IPC. In particular, two new "springs" are introduced: a 'variable rest length' spring and a 'variable stiffness' spring, that are properly defined in order to maintain the passivity of the IPC and to improve its performances in given situations. Simulations of the resulting control, applied to a defective system and to a simple telemanipulation device, are presented and discussed.