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.

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.

This paper addresses the generation of collision-free trajectories for the autonomous execution of assistive tasks in Robotic Minimally Invasive Surgery (R-MIS). The proposed approach takes into account geometric constraints related to the desired task, like for example the direction to approach the final target and the presence of moving obstacles. The developed motion planner is structured as a two-layer architecture: a global level computes smooth spline-based trajectories that are continuously updated using virtual potential fields; a local level, exploiting Dynamical Systems based obstacle avoidance, ensures collision free connections among the spline control points. The proposed architecture is validated in a realistic surgical scenario.

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.

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.

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.

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.

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.

Symbolic reasoners generate plans which are often not exploiting the robot capabilities and are sensitive to runtime disturbances. This work proposes a scheduler as an interface between a discrete, symbolic plan and a motion control based on constraint optimization. Acting as a local reasoner, the scheduler valuates a set of predicates to decide when an action will be executed. Given a task specification which describes how the action should be realized, the scheduler configures the controller at runtime. A demonstration will be provided considering an “open drawer” scenario.

We present our Abstraction Layer Object-Oriented Architecture (ALOOA) and its application to Motion Control. This layer provides a higher level of abstraction than that provided by the well-known PLCOpen library. In fact, the proposed approach uses OO features (i.e. methods, inheritance, and polymorphism) which allow us to define a generic device of motion control, whose hardware-dependent implementation details are then developed with specific Function Blocks (FBs) and methods. We are currently developing and using in our software the ALOOA and its libraries. As result, we can create hardware-independent software applications. Additionally, we achieved a reuse degree of our code of about 70% and improved its maintainability. ALOOA approach could be used to simplify and/or fulfill the maintainability, life-cycle-management, and the specific-platforms-and-their-limitations challenges. Moreover, it could help the OO features to penetrate further into the PLC world.

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.

The paper describes a motion planning and control software architecture developed for the automation of a surgical robot. The considered surgical robot is a dual-arm prototype developed with a redundant and modular mechanical structure, designed to be reconfigured for different surgical tasks, and with a hybrid parallel/serial kinematics. The motion planning solution proposed in the paper includes both an online collision-free path planner, based on the RRT-Connect algorithm, and a generator of predefined motion primitives. This solution allows the multi-arm robot to autonomously execute the complex motion patterns required for a suturing task. Since such motion patterns are specified in the Cartesian space, an efficient and univocal solution of the inverse kinematics of the robot, which is a challenging problem due to its hybrid structure, is another crucial issue addressed in the paper.

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.

We developed an UML-State-charts Object Oriented Design Pattern for PLCs IEC61131-3. This PLC UML-State-chart Design Pattern aims to explore the advantage of Object Oriented Programming by IEC61131-3 in PLCs, and to provide a direct map of UML State-chart to PLC code. We illustrates the design pattern and its use through UML Class diagrams and an application example. This Design Pattern can be used to reduce the development time of State-charts in automation software. It can also lead towards further investigations in PLC Design Patterns that may improve the whole development of automation software.

Combining tasks, melding their activities in sequence and in parallel, in order to achieve the desired goal is a challenging research topic. In many practical applications, tasks could be fulfilled even though the robot does not achieve a perfect matching with a given quantitative objective. Thus, it could be possible to carry out other activities, mildly conflicting with the current goal, yet providing benefits for the overall execution of a complex sequence of tasks. This paper proposes i) a criteria to evaluate the execution of a monitored task, ii) an enriched task specification to express the tolerance with which a goal is fulfilled, so that iii) a sequence of tasks can be executed concurrently, on the basis of monitored quantities. Furthermore, the paper reports a classification of conflicting scenarios for a finer selection of the scheduler policy. Finally, results from experimental scenarios show the potential benefits of the proposed methodology.

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.

Task specification models define the activities to be executed by a robot in order to achieve its goal. Classical examples are the sequences involved in assembly or pick and place tasks. This work introduces the preview coordination execution model, an extension to the traditional way in which the execution of such task specifications is coordinated at runtime. Instead of taking activities one-by-one as defined in the task specification model, preview coordination optimizes the task scheduling based on knowledge about the likelihood that not just the activities required by the current state can be executed, but that also one or more of those related to future states of the system can be activated. An experiment with mobile manipulation tasks illustrates the benefits of preview coordination.

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.

The paper describes the design and implementation of a robot control system on a hardware platform based on a Programmable Logic Controller (PLC). The controlled robot is a 4 degrees of freedom (DOF) manipulator with a closed kinematic chain, designed for high-performance pick and place applications in a packaging workcell. The control software is fully developed on a commercial PLC system, using its standard programming tools and the multi-tasking features of its operating system. In particular, the paper analyse in detail the drawbacks and the advantages related to the choice of standard PLCs in this kind of applications, compared to the much common choice of specialized hardware or industrial personal computers, with particular emphasis on the computational performances obtained with the proposed control architecture.

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

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.

The paper describes a methodological framework that aims to apply formal design and verification techniques in the development of industrial control systems, with particular regard to the domain of manufacturing machines. The methodology is based on an object-oriented approach, revisited in a mechatronic perspective, and is supported by the specification methods proposed by the UML language. This language, opportunely adapted to the application domain, permits to describe control system design models which are modular, reusable and independent from the implementation architecture. The implementation domain is taken into account only during the verification phase, in which it is necessary to identify a correct semantical interpretation according to the execution model of the computational platform. In particular, the different frameworks of the industrial standards IEC 61131-3 and IEC 61499 are considered and compared with each other. The paper shows that formal verification techniques can be applied to prove the correctness of the design specification or to guide its iterative refinement, thanks to a translation of the O-O model into the input language of the model checking tool SMV.

This paper presents a practical experiment on the use of visual servoing for robotic tracking and manipulation of objects moving on a plane. In this work, the image is acquired from the camera mounted on the end-effector of a 6 DOF industrial robot, and processed on a standard PC-based vision system in order to close the visual servoing loop with a PID based controller. The PID has been implemented with a variable structure, modified according to the estimated velocity of the target, in order to achieve a good step response and to eliminate steady-state error with a moving target. The possibility to perform a stable tracking and to estimate the target dynamics allows also to grasp the object with a prediction based trajectory planning.