Anticipatory Robot Assistance for the Prevention of Human Static Joint Overloading in Human–Robot Collaboration

Kim, Wansoo; Lee, Jinoh; Peternel, Luka; Tsagarakis, Nikos G.; Ajoudani, Arash

doi:10.1109/lra.2017.2729666

Cited by 99 publications

(96 citation statements)

References 30 publications

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“…The capability of the model to monitor the progression of fatigue in real-time is then presented for ten subjects performing a painting task with a light-weight tool. Finally, the proposed model is integrated into the HRC framework we presented in [21] to set the timing for the body configuration optimisation and thus to trigger the collaborative robot assistance by the time fatigue is accumulated excessively in some joint.…”

Section: Verification Of the Methodsmentioning

confidence: 99%

“…Several constraints, such as joint limits of the human, postural stability of the human, the position of the object, etc. (a detailed explanation can be found in [21]), were considered in the numerical optimisation process. As a result, an optimal body configuration was computed and robot trajectories were adjusted accordingly, to facilitate the subject to achieve such ergonomic configurations.…”

Section: Overloading Fatigue Mitigation Through Hrcmentioning

confidence: 99%

“…A principled simplification approach was used here which neglects the gravity effect but reduces the number of subject parameters to be identified, avoiding the use of standard data and, above all, it addresses real-time compatibility. Such a model was integrated in a HRC control framework, by which a collaborative robot continuously adjusted the human counterpart's postures to perform a heavy manipulation task in an ergonomic way [21]. A direct application of our previous method would not be suitable in the mitigation of risks associated to repetitive light-weight tasks since the estimated overloading joint torques are low/moderate and the associated risk of joint injuries is not high.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A New Overloading Fatigue Model for Ergonomic Risk Assessment with Application to Human-Robot Collaboration

Lorenzini

Kim

Momi

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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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.

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Section: Verification Of the Methodsmentioning

confidence: 99%

Section: Overloading Fatigue Mitigation Through Hrcmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A New Overloading Fatigue Model for Ergonomic Risk Assessment with Application to Human-Robot Collaboration

Lorenzini

Kim

Momi

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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“…The applications of pHRI are multifarious: carrying and installing heavy objects (Kim et al, 2017;Lee et al, 2007), hand-over (Strabala et al, 2013), cooperative manipulation and manufacturing (Peternel et al, 2014;Cherubini et al, 2016), and assistive tele-operation . While the field of pHRI is rapidly expanding, the role of most robots in the interaction falls into two extreme cases:…”

Section: Related Workmentioning

confidence: 99%

A dynamical system approach to task-adaptation in physical human–robot interaction

Khoramshahi

Billard

2018

Auton Robot

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The goal of this work is to enable robots to intelligently and compliantly adapt their motions to the intention of a human during physical Human-Robot Interaction (pHRI) in a multi-task setting. We employ a class of parameterized dynamical systems that allows for smooth and adaptive transitions between encoded tasks. To comply with human intention, we propose a mechanism that adapts generated motions (i.e., the desired velocity) to those intended by the human user (i.e., the real velocity) thereby switching to the most similar task. We provide a rigorous analytical evaluation of our method in terms of stability, convergence, and optimality yielding an interaction behavior which is safe and intuitive for the human. We investigate our method through experimental evaluations ranging in different setups: a 3-DoF haptic device, a 7-DoF manipulator and a mobile platform.Keywords Physical human-robot interaction · Adaptive behavior · Compliant control · Dynamical systems · Predictive models All authors are with the Learning Algorithms and System-

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“…Among the works that do consider a full human model, there have been applications in: optimizing human comfort in selecting handoff configurations [5], offline trajectory optimization for predicting the motion of an exoskeleton-assisted human [6], finding configurations for a fixed-base manipulator that minimize human exertion in a co-manipulation task [7]. These methods are used for higher-level planning and/or only consider kinematic data.…”

Section: A Related Workmentioning

confidence: 99%

Generating Assistive Humanoid Motions for Co-Manipulation Tasks with a Multi-Robot Quadratic Program Controller

Otani

Bouyarmane

Ivaldi

2018

2018 IEEE International Conference on Robotics and Automation (ICRA)

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Human-humanoid collaborative tasks require that the robot take into account the goals of the task, interaction forces with the human, and its own balance. We present a formulation for a real-time humanoid controller which allows the robot to keep itself stable, while also assisting the human in achieving their shared objectives. We achieve this with a multirobot quadratic program controller, which solves for human motion reconstruction and optimal robot controls in a single optimization problem. Our experiments on a simulated robot platform demonstrate the ability to generate interaction motions and forces that are similar to what a human collaborator would produce.

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Anticipatory Robot Assistance for the Prevention of Human Static Joint Overloading in Human–Robot Collaboration

Cited by 99 publications

References 30 publications

A New Overloading Fatigue Model for Ergonomic Risk Assessment with Application to Human-Robot Collaboration

A New Overloading Fatigue Model for Ergonomic Risk Assessment with Application to Human-Robot Collaboration

A dynamical system approach to task-adaptation in physical human–robot interaction

Generating Assistive Humanoid Motions for Co-Manipulation Tasks with a Multi-Robot Quadratic Program Controller

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