In the current industrial context, the importance of assessing and improving workers’ health conditions is widely recognised. Both physical and psycho-social factors contribute to jeopardising the underlying comfort and well-being, boosting the occurrence of diseases and injuries, and affecting their quality of life. Human-robot interaction and collaboration frameworks stand out among the possible solutions to prevent and mitigate workplace risk factors. The increasingly advanced control strategies and planning schemes featured by collaborative robots have the potential to foster fruitful and efficient coordination during the execution of hybrid tasks, by meeting their human counterparts’ needs and limits. To this end, a thorough and comprehensive evaluation of an individual’s ergonomics, i.e. direct effect of workload on the human psycho-physical state, must be taken into account. In this review article, we provide an overview of the existing ergonomics assessment tools as well as the available monitoring technologies to drive and adapt a collaborative robot’s behaviour. Preliminary attempts of ergonomic human-robot collaboration frameworks are presented next, discussing state-of-the-art limitations and challenges. Future trends and promising themes are finally highlighted, aiming to promote safety, health, and equality in worldwide workplaces.
Prolonged remote tele-locomanipulation of multi degrees-of-freedom mobile manipulators requires a compromise between the system's performance and the operator's ergonomics. Neglecting this demand can significantly affect either the task completion or the level of comfort to achieve it. However, the simultaneous consideration of these key factors has received less attention in the literature. To respond to this demand, in this work, we introduce a new teleoperation setup, which integrates the features of an ergonomic and a highly maneuverable interface into a unified solution. The ergonomic part of the interface implements a 3D mouse-like functionality, enabling the execution of long navigation tasks for the floating base. The highly manoeuvrable interface instead, enables the operator to perform dynamic or more precise manipulation by moving his/her arm in space. The locomotion and manipulation modes of the follower robot are controlled separately, which can be easily and seamlessly switched by the operator by pressing a button at any moment. Furthermore, due to the follower manipulator's redundancy, this robot is controlled by a hierarchical quadratic programming technique which enables the definition of a set of secondary tasks to be executed in the robot's nullspace. Finally, to demonstrate the advantages and disadvantages of the proposed user interfaces, five participants are asked to perform two different experiments: (i) target selection task on a moving surface and (ii) remote path tracking on a fixed surface. The quantitative and qualitative analyses show the effectiveness of the proposed interface during the teleoperation tasks, especially when it comes to the precise and dynamic task execution.
In this manuscript, we present an online scalable tele-impedance framework, which enables the individual and collaborative control of multiple different robotic platforms. The framework provides an intuitive low-cost interface with visual feedback and a SpaceMouse, through which the operator can define the desired task-level trajectories and impedance profiles. With a simple SpaceMouse click, the user can switch between the robots and the collaborative operation mode. The control, subsequently, manages the distribution of the required parameters into the involved robots. Thanks to the introduced virtual hand concept where each robot is defined as a finger, new robots can be easily added or removed via their kinodynamic parameters. The proposed framework was evaluated with three different experiments: a simulated auscultation on a mock-up patient, a cooperative task where a robot drives the patient on a wheelchair and a different robot performs the auscultation, and a collaborative task where two robots relocate a container. The results demonstrate the capabilities of the framework in terms of adaptability to different robotic platforms, the number of robots involved, and the task requirements. Additionally, quantitative and subjective analysis of 12 subjects showed how the developed interface, even in the presence of inaccurate visual feedback, allowed a smooth and accurate execution of the tasks.
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