A model‐based strategy for safety assessment of a robot arm interacting with humans

Kovincic, Nemanja; Gattringer, Hubert; Müller, Andreas; Weyrer, Matthias; Schlotzhauer, Andreas; Kaiser, Lukas; Brandstötter, Mathias

doi:10.1002/pamm.201900247

Cited by 11 publications

(11 citation statements)

References 2 publications

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“…In ref. [28], the Coulomb friction term is smoothed by an hyperbolic function, so as to avoid a discontinuity at null speed. The same model, with the addition of a Stribeck friction torque is the choice of works [42,54], with the letter requiring the determination of 24 parameters for modeling dissipative forces.…”

Section: Figure 8 Validation Of Estimated Values Of Motor and Gearbox...mentioning

confidence: 99%

“…Friction appears to be related to several operating conditions [34], and in lightweight collaborative robots is mainly due to the losses in the strain wave gearboxes. The friction model can be arbitrarily simplified, as much as describing it only by means of the viscous and Coulomb terms without any major modeling error [28]. Nonetheless, a higher accuracy seems to be achievable by considering also the dependence to load [35,36] and temperature [37].…”

Section: Introductionmentioning

confidence: 99%

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Electro-mechanical modeling and identification of the UR5 e-series robot

Clochiatti,

Scalera,

Boscariol

et al. 2024

Robotica

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Collaborative robotics is a field of growing industrial interest, within which understanding the energetic behavior of manipulators is essential. In this work, we present the electro-mechanical modeling of the UR5 e-series robot through the identification of its dynamics and electrical parameters. By means of the identified robot model, it is then possible to compute and optimize the energy consumption of the robot during prescribed trajectories. The proposed model is derived from data acquired from the robot controller during bespoke experimental tests, using model identification procedures and datasheet provided by manipulator, motors, and gearbox manufacturers. The entire procedure does not require the use of any additional sensor, so it can be easily replicated with an off-the-shelf manipulator, and applied to other robots of the same family.

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Section: Figure 8 Validation Of Estimated Values Of Motor and Gearbox...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Electro-mechanical modeling and identification of the UR5 e-series robot

Clochiatti,

Scalera,

Boscariol

et al. 2024

Robotica

View full text Add to dashboard Cite

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“…Calculating the impact force of a human-robot collision using the above-presented equation of motion requires data, such as mass inertia, centripetal, and Coriolis terms, which are usually not provided to the end user [26]. In [11], a simplified two-mass system is used to simulate a transient human-robot collision (Fig.…”

Section: A State Of the Art Formal Verification Of Human-robot Collis...mentioning

confidence: 99%

Collision Tests in Human-Robot Collaboration: Experiments on the Influence of Additional Impact Parameters on Safety

Fischer,

Neuhold,

Steiner

et al. 2023

IEEE Access

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Human-robot collaborations are among the most promising but challenging applications for human-centered production, as both agents involved share a mutual workspace without physical barriers. Safety aspects require limiting the power and force of operations to comply with biomechanical limits in case of a collision according to the International Organization for Standardization (ISO) technical specification ISO/TS 15066:2016. This analysis requires highly elaborate physical crash tests of potential impact scenarios. Formal verification will save considerable amounts of time and effort. However, the equations presented in current guidelines need to be more accurate as many factors influencing the impact force and pressure are not considered, making these equations impractical for the evaluation of real applications. To answer the question of which parameters influence a human-robot collision, we have experimentally analyzed different collision scenarios in various configurations. The main results show the correlation of impactor geometries, edges versus rounding, and Shore hardness of the affected body region that simulates human tissue. This work presents the parameters that a formal human-robot collision verification model should contain, based on experimental tests. Furthermore, a model that identifies a collision's worst-case impacted body region is introduced. The results of this work will help in simplifying and accelerating the safety evaluation process of collaborative human-robot applications to better realize their potential.INDEX TERMS Industrial robot safety, human-robot collaboration (HRC), formal methods in robotics and automation, power and force limitation, robot collision evaluation.

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“…However, this is feasible only if the gearbox is mounted on a specific test bench and properly sensorized. An alternative approach, which does not require dismounting the harmonic drive from the robot arm, is based on the dynamic parameters identification of the manipulator (Kovincic, Müller, Gattringer, Weyrer, Schlotzhauer & Brandstötter, 2019). This procedure allows estimating both Coulomb and viscous friction coefficients for each joint.…”

Section: Lubricationmentioning

confidence: 99%

Harmonic Drive Gear Failures in Industrial Robots Applications: An Overview

et al. 2021

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Industrial robots play a key role in production lines. As a direct consequence, even a slight degradation of their operating conditions could negatively affect the entire manufacturing process. To minimize economical losses, preventive measures such as planned maintenance or stand-by working stations are adopted and, in some cases, additional manipulators are installed to ensure line availability. However, since each robot performs a specific task, it degrades at a different rate from another one, so Planned Preventive Maintenance (PPM) should be replaced with Condition Based Maintenance (CBM) for a more efficient and cost-effective approach. In addition, collaborative robots (cobots) have become more and more popular in the past years increasing the level of automation, in particular in small and medium size companies. Therefore, a failure of an industrial manipulator could not only cause unexpected downtimes, but also jeopardize the safety of the personnel with whom it shares its workspace. A cobot, in fact, is labeled as safe as long as it works in nominal conditions, but this cannot be guaranteed otherwise. Within this framework, Prognostics and Health Management (PHM) techniques could be used for both a customized maintenance on a specific machine and for preventing undesired events like the aforementioned ones. An ongoing research activity at Politecnico di Torino is focused on a model-based approach able to better describe the behavior of an industrial robot in non-nominal operating conditions. In order to properly simulate faults and failures of a manipulator, it has been first necessary to analyze its failure modes and their impact on the entire system. A robot, in fact, is usually equipped with internal sensors and algorithms able to monitor its health status. However, this is only true for software or electrical failures (i.e. power supply, motor or sensors related), but it is not as effective in case of mechanical ones like bearings or gearbox wear. This paper firstly presents an overview of the possible failures related to harmonic drives which are often used in robotics due to their compact and light-weight design and the high reduction ratio. Then, it outlines the work done with the objective of providing an accurate, physics-based description of faults progression of harmonic drives used in industrial robots and the related high-fidelity models in the framework of a PHM system for fault and failure detection, isolation and remaining useful life (RUL) prediction.

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A model‐based strategy for safety assessment of a robot arm interacting with humans

Cited by 11 publications

References 2 publications

Electro-mechanical modeling and identification of the UR5 e-series robot

Electro-mechanical modeling and identification of the UR5 e-series robot

Collision Tests in Human-Robot Collaboration: Experiments on the Influence of Additional Impact Parameters on Safety

Harmonic Drive Gear Failures in Industrial Robots Applications: An Overview

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