Federico Vicentini

Safe Human-Robot Cooperation in an Industrial Environment

The standard EN ISO10218 is fostering the implementation of hybrid production systems, i.e., production systems characterized by a close relationship among human operators and robots in cooperative tasks. Human-robot hybrid systems could have a big economic benefit in small and medium sized production, even if this new paradigm introduces mandatory, challenging safety aspects. Among various requirements for collaborative workspaces, safety-assurance involves two different application layers; the algorithms enabling safe space-sharing between humans and robots and the enabling technologies allowing acquisition data from sensor fusion and environmental data analysing. This paper addresses both the problems: a collision avoidance strategy allowing on-line re-planning of robot motion and a safe network of unsafe devices as a suggested infrastructure for functional safety achievement.

Deformation-tracking impedance control in interaction with uncertain environments

A deformation-tracking impedance control strategy is discussed for applications where a manipulator interacts with environments of unknown geometrical and mechanical properties, especially with stiffness comparable to a controlled robot stiffness. Based on force-tracking impedance controls, the deformation-tracking strategy allows the control of a desired deformation of the target environment, requiring the on-line estimation of the environment stiffness. An Extended Kalman Filter is used for the estimation of the environment because of measurement uncertainties and errors in compound interaction model. The tasks presented involve full body spatial interactions with a time-varying environment stiffness. The Extended Kalman Filter and the deformation-tracking impedance control are validated in simulation and with experiments. In particular, a cooperative assembly task is also performed with a human operator acting as varying environment, i.e. unpredictably changing the handling arm stiffness.

Optimal Impedance Force-Tracking Control Design With Impact Formulation for Interaction Tasks

The letter presents a force-tracking impedance controller granting a free-overshoots contact force (mandatory performance for many critical interaction tasks such as polishing) for partially unknown interacting environments (such as leather or hard-fragile materials). As in many applications, the robot has to gently approach the target environment (whose position is usually not well-known), then execute the interaction task. Therefore, the algorithm has been designed to deal with both the free space approaching motion (phase a.) and the succeeding contact task (phase b.) without switching from different control logics. Control gains have to be properly calculated for each phase in order to achieve the target force tracking performance (i.e., free-overshoots contact force). In detail, phase a. control gains are optimized based on the impact collision model to minimize the force error during the following contact task, while phase b. control gains are analytically calculated based on the solution of the LQR optimal control problem. The analytical solution grants the continuous adaptation of the control gains during the contact phase on the estimated value of the environment stiffness (obtained through an on-line extended Kalman filter). A probing task has been carried out to validate the performance of the control with partially unknown contact environment properties. Results show the avoidance of force overshoots and instabilities.

Normative Data for an Instrumental Assessment of the Upper-Limb Functionality

Upper-limb movement analysis is important to monitor objectively rehabilitation interventions, contributing to improving the overall treatments outcomes. Simple, fast, easy-to-use, and applicable methods are required to allow routinely functional evaluation of patients with different pathologies and clinical conditions. This paper describes the Reaching and Hand-to-Mouth Evaluation Method, a fast procedure to assess the upper-limb motor control and functional ability, providing a set of normative data from 42 healthy subjects of different ages, evaluated for both the dominant and the nondominant limb motor performance. Sixteen of them were reevaluated after two weeks to perform test-retest reliability analysis. Data were clustered into three subgroups of different ages to test the method sensitivity to motor control differences. Experimental data show notable test-retest reliability in all tasks. Data from older and younger subjects show significant differences in the measures related to the ability for coordination thus showing the high sensitivity of the method to motor control differences. The presented method, provided with control data from healthy subjects, appears to be a suitable and reliable tool for the upper-limb functional assessment in the clinical environment.

Leveraging RF signals for human sensing: Fall detection and localization in human-machine shared workspaces

Safe human-machine interactions promote high flexibility in collaborative workspaces. Fall detection and localization of the operator are major issues in ensuring a safe working environment. However, many proposed solutions are not applicable for deployment in industrial environments due to their performance limitations in practical contexts. In this paper, we propose an integrated framework for both localization and fall detection of operators inside a shared workspace that employs radio-frequency (RF) signal analysis in real-time. Multipath and non-line-of-sight (NLOS) scattering that affect RF signal propagation can be leveraged for human sensing in complex workspaces: the proposed system continuously monitors the fluctuations of the RF field across the space by a dense network of WiFi compliant radio devices operating at 2.4GHz. To increase the accuracy of the localization system, a sensor fusion algorithm using Extended Kalman Filter techniques is employed. The proposed method may be used for integrating measurements from both RF nodes and an additional image-based system. For fall detection, a Hidden Markov Model is applied to discern different postures of the operator and to detect a fall event by tracking the fluctuations of the wireless signal quality. Fall detector performances are validated through experimental measurements. The preliminary results confirm the effectiveness of the proposed approach for different body configurations and pre-impact postures to correctly detect a fall event. Finally, some results about sensor fusion for improved operator localization are presented.

Device-Free Human Sensing and Localization in Collaborative Human–Robot Workspaces: A Case Study

Modern robot manufacturing is fostering the implementation of hybrid production systems characterized by human-robot cooperative tasks. Safety technologies for workers protection require advanced sensing capabilities and flexible solutions that are able to monitor the movements of the operator in proximity of moving robots. This paper proposes the use of wireless device-free localization (DFL) methods and architectures to detect and track a human worker in a cooperative human-robot industrial workspace. The DFL system is composed of groups of massively interacting small, low-cost, embedded radio-frequency (RF) transceivers that perform received power measurements. These devices are anchored in fixed peripheral locations of the plant and provide the localization of the worker, who peculiarly carries neither wireless active devices (device-free) nor specific tracking sensors (sensor-free sensing). Operator motion is, in fact, estimated by tracking the perturbations of the radio field induced by the human body, considering the effect of concurrently moving robot as non-stationary interference. The proposed localization and detection algorithm is based on the jump linear Markovian system and the interactive multiple model method, and its positioning accuracy has been validated by experiments performed inside a robotic cell of an industrial test plant. The proposed DFL system has been implemented by employing IEEE 802.15.4 RF devices operating at 2.4 GHz and integrated into a software safety architecture. Finally, a software toolset has been designed to predict DFL accuracy, to verify experimental measurements, and also to support the integration with preinstalled industrial sensors to increase the accuracy of the augmented system.

A spherical parallel three degrees-of-freedom robot for ankle-foot neuro-rehabilitation

The ankle represents a fairly complex bone structure, resulting in kinematics that hinders a flawless robot-assisted recovery of foot motility in impaired subjects. The paper proposes a novel device for ankle-foot neuro-rehabilitation based on a mechatronic redesign of the remarkable Agile Eye spherical robot on the basis of clinical requisites. The kinematic design allows the positioning of the ankle articular center close to the machine rotation center with valuable benefits in term of therapy functions. The prototype, named PKAnkle, Parallel Kinematic machine for Ankle rehabilitation, provides a 6-axes load cell for the measure of subject interaction forces/torques, and it integrates a commercial EMG-acquisition system. Robot control provides active and passive therapeutic exercises.

Impedance shaping controller for robotic applications in interaction with compliant environments

The impedance shaping control is presented in this paper, providing an extension of standard impedance controller. The method has been conceived to avoid force overshoots in applications where there is the need to track a force reference. Force tracking performance are obtained tuning on-line both the position set-point and the stiffness and damping parameters, based on the force error and on the estimated stiffness of the interacting environment (an Extended Kalman Filter is used). The stability of the presented strategy has been studied through Lyapunov. To validate the performance of the control an assembly task is taken into account, considering the geometrical and mechanical properties of the environment (partially) unknown. Results are compared with constant stiffness and damping impedance controllers, which show force overshoots and instabilities.

Analysis of elbow-joints misalignment in upper-limb exoskeleton

This paper presents advantages of introducing elbow-joints misalignments in an exoskeleton for upper limb rehabilitation. Typical exoskeletons are characterized by axes of the device as much as possible aligned to the rotational axes of human articulations. This approach leads to advantages in terms of movements and torques decoupling, but can lead to limitations nearby the elbow singular configuration. A proper elbow axes misalignment between the exoskeleton and the human can improve the quality of collaborative rehabilitation therapies, in which a correct torque transmission from human articulations to mechanical joints of the device is required to react to torques generated by the patient.

Impedance Control based Force-tracking Algorithm for Interaction Robotics Tasks: An Analytically Force Overshoots-free Approach

In the presented paper an analytically force overshoots-free approach is described for the execution of robotics interaction tasks involving a compliant (of unknown geometrical and mechanical properties) environment. Based on the impedance control, the aim of the work is to perform force-tracking applications avoiding force overshoots that may result in task failures. The developed algorithm shapes the equivalent stiffness and damping of the closed-loop manipulator to regulate the interaction dynamics deforming the impedance control set-point. The force-tracking performance are obtained defining the control gains analytically based on the estimation of the interacting environment stiffness (performed using an Extended Kalman Filter). The method has been validated in a probing task, showing the avoidance of force overshoots and the achieved target dynamic performance.