Physical Safety in Robotics

Haddadin, Sami

doi:10.1007/978-3-658-09994-7_9

Cited by 24 publications

(9 citation statements)

References 54 publications

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“…2) Risk Estimation: Pain and Pressure: The general principle in HRC physical interaction [64] is that the operator should never get injured. However, ISO/TS 15066 claims that occasional accidental contacts would produce just a sensation of limited pain that is not different from the sensation generated by contacts in activities of daily life and could be captured by Se < 3.…”

Section: B Risk Estimation Modulementioning

confidence: 99%

“…There have been several studies [60], [65]- [67] to set empirical injury scales. Experiments on dummies and cadavers are reported in [64]. Although the biomechanics of pain is far from being fully understood, the primary figure for painful interaction is known to be pressure, i.e., the contact force distributed through the interaction area.…”

Section: B Risk Estimation Modulementioning

confidence: 99%

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Safety Assessment of Collaborative Robotics Through Automated Formal Verification

et al. 2020

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A crucial aspect of physical human-robot collaboration (HRC) is to maintain a safe common workspace for human operator. However, close proximity between human-robot and unpredictability of human behavior raises serious challenges in terms of safety. This article proposes a risk analysis methodology for collaborative robotic applications, which is compatible with well-known standards in the area and relies on formal verification techniques to automate the traditional risk analysis methods. In particular, the methodology relies on temporal logic-based models to describe the different possible ways in which tasks can be carried out, and on fully automated formal verification techniques to explore the corresponding state space to detect and modify the hazardous situations at early stages of system design.Index Terms-Formal methods, human-robot collaboration (HRC), model-based risk assessment, robot safety, temporal logic. I. INTRODUCTIONH UMAN-ROBOT collaboration (HRC) in industrial settings enhances the flexibility and adaptability of robotic systems for production. Close proximity and hybrid task assignment between humans and robots have substantial impacts on the safety of human operators. Most importantly, shared dynamic environments cannot be effectively supported by static safety analyses. In particular, the hybrid human-robot tasks generate different possible execution workflows. Therefore, various task assignments among humans and robots can also change during operations. In realistic scenarios, the environment can also change, due to mobile resources, tool changing, modification of the layout, and process locations, so that the specifications of the system need to be re-evaluated. The safety of such evolving systems should not be verified as a static property, but rather according to the behavior of the system in actual situations.

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Section: B Risk Estimation Modulementioning

confidence: 99%

Section: B Risk Estimation Modulementioning

confidence: 99%

Safety Assessment of Collaborative Robotics Through Automated Formal Verification

et al. 2020

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“…To date, robots have proven to be practical in industry, where they are used for dirty, dull, dangerous, domestic, and dexterous tasks. On the other hand, there is a high level of uncertainty around human-robot interactions [1]. Roboticists attempt to alleviate problems that humans face when working in proximity to robots.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Two Complementary Modeling Approaches for Fiber-Reinforced Soft Actuators

Habibian,

Wheatley,

Bae

et al. 2021

Preprint

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Robots are increasingly used in a wide range of applications. We, as humans, still find it challenging to work in proximity to robots due to safety concerns. In recent years, roboticists have been seeking a solution to this challenge through soft robots. In addition to providing safety in human-robot interactions, soft robots demonstrate favorable characteristics relative to traditional rigid robots: greater compatibility with their unpredictable environments, higher degrees of freedom, and lower manufacturing costs. Unfortunately, it is often challenging to find the optimal model to fully investigate and analyze the behavior of a soft robot. This paper seeks to address this challenge by proposing two complementary modeling techniques for a particular type of soft robotic actuator known as Fiber Reinforced Elastomeric Enclosures (FREEs). We propose that designers can leverage multiple models to fill the gaps in the understanding of soft robots. We develop and test both a dynamic lumped-parameter model and a finite element model in an attempt to understand the practicability of FREEs for use in a soft robotic arm. The resulting insights enabled us to investigate the controllability of FREEs using the dynamic model, and its design parameters and workspace via the finite element model. We evaluated our modeling approaches through simulation and experiments. The results from the lumped-parameter model suggest that at low pressures FREEs approximately maintain their initial winding angle and radius during pressurization. This allowed us to make simplifying assumptions that led to the development of a model-driven controller for a single FREE, although extending this model for a module of multiple FREEs can be challenging. This provided motivation for the development of a finite element model for single and multiple FREE configurations. Our findings indicate that the material properties and winding angles greatly influence FREEs' extension, rotation, and force and moment generation. Additionally, results showed that a 30 • difference in winding angle difference significantly alters the shape of the workspace of multiple FREEs assembled in a module. Overall, both models efficiently predict the behavior of FREEs. Employing two modeling approaches enabled us to fully investigate behavior, whereas neither model individually significantly demonstrates the complete range of FREE capabilities.

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“…In addition to the interaction management, the robot controller should handle several constraints, such as speed and energy limits [8], limited jerk [9] or actuators saturation. These limits allow ensuring safety [10] as well as good ergonomics of the human-robot interaction [11]. However, it is not straightforward to respect these constraints using classical IC.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Impedance Control

Bednarczyk

Omran

Bayle

2020

2020 IEEE International Conference on Robotics and Automation (ICRA)

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Robots are more and more often designed in order to perform tasks in synergy with human operators. In this context, a current research focus for collaborative robotics lies in the design of high-performance control solutions, which ensure security in spite of unmodeled external forces. The present work provides a method based on Model Predictive Control (MPC) to allow compliant behavior when interacting with an environment, while respecting practical robotic constraints. The study shows in particular how to define the impedance control problem as a MPC problem. The approach is validated with an experimental setup including a collaborative robot. The obtained results emphasize the ability of this control strategy to solve constraints like speed, energy or jerk limits, which have a direct impact on the operator's security during human-robot compliant interactions.

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Physical Safety in Robotics

Cited by 24 publications

References 54 publications

Safety Assessment of Collaborative Robotics Through Automated Formal Verification

Safety Assessment of Collaborative Robotics Through Automated Formal Verification

Evaluation of Two Complementary Modeling Approaches for Fiber-Reinforced Soft Actuators

Model Predictive Impedance Control

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