This letter presents a novel teleoperation interface that enables remote loco-manipulation control of a MObile Collaborative robotic Assistant (MOCA). MOCA is a new research platform developed at the Istituto Italiano di Tecnologia (IIT), which is composed of a lightweight manipulator arm, a Pisa/IIT SoftHand, and a mobile platform driven by four omni-directional wheels. A whole-body impedance controller is consequently developed to ensure accurate tracking of the impedance and position trajectories at MOCA end-effector by considering the causal interactions in such a dynamic system. The proposed teleoperation interface provides the user with two control modes: locomotion and manipulation. The locomotion mode receives inputs from a personalized human center-of-pressure model, which enables real-time navigation of the MOCA mobile base in the environment. The manipulation mode receives inputs from a tele-impedance interface, which tracks human arm endpoint stiffness and trajectory profiles in real time and replicates them using the MOCA's whole-body impedance controller. To evaluate the performance of the proposed teleoperation interface in the execution of remote tasks with dynamic uncertainties, a sequence of challenging actions, i.e., navigation, door opening, and wall drilling, has been considered in the experimental setup.

M usculoskeletal disorders, the single largest category of workrelated injuries in many industrial countries, are associated with very high costs in terms of lost productivity. In highvolume production facilities, large parts of the workstation should ideally be adapted to individual workers in real time to prevent such injuries. However, in smaller production lines, especially those found in small and medium enterprises (SMEs), regularly adapting the entire workstation to accommodate flexibility is a major challenge. A solution to the problem is the development of reconfigurable human-robot collaboration (HRC) workstations and frameworks. These are key to enabling agile manufacturing, by merging the dexterity, flexibility, and ©ISTOCKPHOTO.COM/ALASHI

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Among the numerous risk factors associated to work-related musculoskeletal disorders (WMSD), repetitive and monotonous movements with light-weight tools are one of the most frequently cited. Such tasks may indeed result in the excessive accumulation of local muscle fatigue, causing severe injuries in human joints. Accordingly, this paper proposes a new whole-body fatigue model to evaluate the cumulative effect of the overloading torque induced on the joints over time by light payloads. The proposed model is then integrated into a human-robot collaboration (HRC) framework to set the timing of a body posture optimisation procedure guided by the robot assistance, by the time fatigue overcomes a threshold in any joint. Our overloading fatigue model is based on an estimation method we developed in a previous work, to monitor joint torque variations due to external forces in real-time. To account for individuals' different perception of fatigue, the fatigue ratio parameter in the model is computed experimentally for each subject. The proposed model is first studied on ten subjects by means of an electromyography analysis. Next, its performance is assessed in a painting task and finally evaluated within the HRC framework, which is proved to be able to reduce the risk of injuries caused by excessive fatigue accumulation.

The success of robots in real-world environments is largely dependent on their ability to interact with both humans and said environment. The FP7 EU project CoDyCo focused on the latter of these two challenges by exploiting both rigid and compliant contacts dynamics in the robot control problem. Regarding the former, to properly manage interaction dynamics on the robot control side, an estimation of the human behaviours and intentions is necessary. In this paper we present the building blocks of such a human-in-the-loop controller, and validate them in both simulation and on the iCub humanoid robot using a human-robot interaction scenario. In this scenario, a human assists the robot in standing up from being seated on a bench. Index Terms-Physical Human-Robot Interaction, Humanoid Robots I. INTRODUCTION T HE ability to interact with and manipulate the environment gives robots a distinct advantage over purely software based automated agents. In the FP7 European project, CoDyCo, the focus was on how to properly exploit contact dynamics in the control of the robot. When the interaction involves humans, their intrinsic unpredictability makes the collaboration problem far more difficult. Foreseen robotic applications range from the use of robots as service and elderly assistants, to their use in industrial plants in close contact with

Physical human-robot interaction is receiving a growing attention from the scientific community. One of the main challenges is to understand the principles governing the mutual behaviour during collaborative interactions between humans. In this context, the knowledge of human whole-body motion and forces plays a pivotal role. Current state of the art methods, however, do not allow one for reliable estimations of the human dynamics during physical human-robot interaction. This paper builds upon our former work on human dynamics estimation by proposing a probabilistic framework and an estimation tool for online monitoring of the human dynamics during human-robot collaboration tasks. The soundness of the proposed approach is verified in human-robot collaboration experiments and the results show that our probabilistic framework is able to estimate the human dynamic, thereby laying the foundation for more complex collaboration scenarios.

The objective of this paper is to develop and evaluate a directional vibrotactile feedback interface as a guidance tool for postural adjustments during work. In contrast to the existing active and wearable systems such as exoskeletons, we aim to create a lightweight and intuitive interface, capable of guiding its wearers towards more ergonomic and healthy working conditions. To achieve this, a vibrotactile device called ErgoTac is employed to develop three different feedback modalities that are able to provide a directional guidance at the body segments towards a desired pose. In addition, an evaluation is made to find the most suitable, comfortable, and intuitive feedback modality for the user. Therefore, these modalities are first compared experimentally on fifteen subjects wearing eight ErgoTac devices to achieve targeted arm and torso configurations. The most effective directional feedback modality is then evaluated on five subjects in a set of experiments in which an ergonomic optimisation module provides the optimised body posture while performing heavy lifting or forceful exertion tasks. The results yield strong evidence on the usefulness and the intuitiveness of one of the developed modalities in providing guidance towards ergonomic working conditions, by minimising the effect of an external load on body joints. We believe that the integration of such lowcost devices in workplaces can help address the well-known and complex problem of work-related musculoskeletal disorders.