Validating Safety in Human–Robot Collaboration: Standards and New Perspectives

Valori, Marcello; Scibilia, Adriano; Fassi, Irene; Saenz, José; Behrens, Roland; Herbster, Sebastian; Bidard, C.; Lucet, Éric; Magisson, Alice; Schaake, Leendert; Bessler, Jule; Prange-Lasonder, Gerdienke B.; Kühnrich, Morten; Lassen, Aske Bach; Nielsen, Kurt Gammelgaard

doi:10.3390/robotics10020065

Cited by 47 publications

(33 citation statements)

References 15 publications

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“…This is supporting the need for carefully considering hazards associated with not only translational but also rotational misalignments during wearable robot development and use. To support robot developers in validation of this and other safety aspects, the European project COVR provides procedures for validation tests in an online Toolkit ( www.safearoundrobots.com ) [ 26 , 27 ]. Future research can increase this knowledge by investigating more conditions and exploring options to develop improved limb simulators.…”

Section: Discussionmentioning

confidence: 99%

Assessing effects of exoskeleton misalignment on knee joint load during swing using an instrumented leg simulator

Bessler

Schaake

Prange-Lasonder

et al. 2022

J NeuroEngineering Rehabil

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Background Exoskeletons are working in parallel to the human body and can support human movement by exerting forces through cuffs or straps. They are prone to misalignments caused by simplified joint mechanics and incorrect fit or positioning. Those misalignments are a common safety concern as they can cause undesired interaction forces. However, the exact mechanisms and effects of misalignments on the joint load are not yet known. The aim of this study was therefore to investigate the influence of different directions and magnitudes of exoskeleton misalignment on the internal knee joint forces and torques of an artificial leg. Methods An instrumented leg simulator was used to quantify the changes in knee joint load during the swing phase caused by misalignments of a passive knee brace being manually flexed. This was achieved by an experimenter pulling on a rope attached to the distal end of the knee brace to create a flexion torque. The extension was not actuated but achieved through the weight of the instrumented leg simulator. The investigated types of misalignments are a rotation of the brace around the vertical axis and a translation in anteroposterior as well as proximal/distal direction. Results The amount of misalignment had a significant effect on several directions of knee joint load in the instrumented leg simulator. In general, load on the knee joint increased with increasing misalignment. Specifically, stronger rotational misalignment led to higher forces in mediolateral direction in the knee joint as well as higher ab-/adduction, flexion and internal/external rotation torques. Stronger anteroposterior translational misalignment led to higher mediolateral knee forces as well as higher abduction and flexion/extension torques. Stronger proximal/distal translational misalignment led to higher posterior and tension/compression forces. Conclusions Misalignments of a lower leg exoskeleton can increase internal knee forces and torques during swing to a multiple of those experienced in a well-aligned situation. Despite only taking swing into account, this is supporting the need for carefully considering hazards associated with not only translational but also rotational misalignments during wearable robot development and use. Also, this warrants investigation of misalignment effects in stance, as a target of many exoskeleton applications.

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Section: Discussionmentioning

confidence: 99%

Assessing effects of exoskeleton misalignment on knee joint load during swing using an instrumented leg simulator

Bessler

Schaake

Prange-Lasonder

et al. 2022

J NeuroEngineering Rehabil

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“…The regulatory landscape for robot devices are, on the contrary, currently populated by a myriad of technology-neutral regulations (Leenes et al, 2017), abstract codes of conduct, and trustworthy-based ethical guidelines (HLEG AI, 2019b) that lack the necessary empirical grounding to inform researchers, designers, and developers’ practices adequately. Accordingly, they fail to tackle the complex problem of giving appropriate guidance to robot developers, who often face the task of developing design measures to make robots fit those abstract values (Lipton, 2018; Valori et al, 2021). Not rarely do developers find themselves in a position with unclear regulatory guidance and in which they usually end up not integrating policy goals entirely.…”

Section: The Difficulties Of Regulating Emerging Robots: Lack Of Info...mentioning

confidence: 99%

Harnessing robot experimentation to optimize the regulatory framing of emerging robot technologies

2022

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From exoskeletons to lightweight robotic suits, wearable robots are changing dynamically and rapidly, challenging the timeliness of laws and regulatory standards that were not prepared for robots that would help wheelchair users walk again. In this context, equipping regulators with technical knowledge on technologies could solve information asymmetries among developers and policymakers and avoid the problem of regulatory disconnection. This article introduces pushing robot development for lawmaking (PROPELLING), an financial support to third parties from the Horizon 2020 EUROBENCH project that explores how robot testing facilities could generate policy-relevant knowledge and support optimized regulations for robot technologies. With ISO 13482:2014 as a case study, PROPELLING investigates how robot testbeds could be used as data generators to improve the regulation for lower-limb exoskeletons. Specifically, the article discusses how robot testbeds could help regulators tackle hazards like fear of falling, instability in collisions, or define the safe scenarios for avoiding any adverse consequences generated by abrupt protective stops. The article’s central point is that testbeds offer a promising setting to bring policymakers closer to research and development to make policies more attuned to societal needs. In this way, these approximations can be harnessed to unravel an optimal regulatory framework for emerging technologies, such as robots and artificial intelligence, based on science and evidence.

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“…Safety emerges as a still open research field, despite the numerous studies that already had tackled this particular issue. We refer the reader to the following reviews on the requirements and challenges of safety in HRC [3,5,7,[38][39][40][41][42][43]. Some reported studies approach the safety problem by assuming the human operators and the robots share the same workspace but perform different tasks.…”

Section: Safety In Hrcmentioning

confidence: 99%

Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics

Castro

Silva

Santos

2021

Sensors

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Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between a human operator and a robot, representing one of the most significant subjects for human-life improvement.The ultimate goal is to achieve physical interaction, where handing over an object plays a crucial role for an effective task accomplishment. Considerable research work had been developed in this particular field in recent years, where several solutions were already proposed. Nonetheless, some particular issues regarding Human-Robot Collaboration still hold an open path to truly important research improvements. This paper provides a literature overview, defining the HRC concept, enumerating the distinct human-robot communication channels, and discussing the physical interaction that this collaboration entails. Moreover, future challenges for a natural and intuitive collaboration are exposed: the machine must behave like a human especially in the pre-grasping/grasping phases and the handover procedure should be fluent and bidirectional, for an articulated function development. These are the focus of the near future investigation aiming to shed light on the complex combination of predictive and reactive control mechanisms promoting coordination and understanding. Following recent progress in artificial intelligence, learning exploration stand as the key element to allow the generation of coordinated actions and their shaping by experience.

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Validating Safety in Human–Robot Collaboration: Standards and New Perspectives

Cited by 47 publications

References 15 publications

Assessing effects of exoskeleton misalignment on knee joint load during swing using an instrumented leg simulator

Assessing effects of exoskeleton misalignment on knee joint load during swing using an instrumented leg simulator

Harnessing robot experimentation to optimize the regulatory framing of emerging robot technologies

Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics

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