A HMM-based approach to learning probability models of programming strategies for industrial robots

Hollmann, Rebecca; Rost, Arne; Hägele, Martin; Verl, Alexander

doi:10.1109/robot.2010.5509888

Cited by 4 publications

(6 citation statements)

References 12 publications

(8 reference statements)

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“…Lead-through programming -standard used in industrial settings, together with OLP -[96]- [98]: usability assessment -[100]- [103]: improved with intuitive input devices (comparative overview in [13]) Off-line programming -standard used in industrial settings -refinements with lead-through programming still necessary - [13], [104]: review of the method and its variants -[106]- [109]: approaches and issues related to robot calibration Walk-through programming -[6], [12], [110]- [120], [124], [125], [127], [128]: force/torque sensing -- [6], [12], [113]- [117], [124], [125]: admittance/impedance control schemes -- [118], [119], [127], [128]: variable admittance/impedance control -- [120]: force control - [110], [124], [125]: introduction of a virtual tool - [35], [130], [131]: techniques alternative to force/torque sensing to detect intentional interaction -[121]- [123]: preliminary industrial applications Programming by demonstration - [8], [139]: overview and classification - [133], [134]: symbolic encoding - [135], [136]: trajectory encoding - [145]: preliminary industrial applications…”

Section: Robot Programmingmentioning

confidence: 99%

“…However, most of works related to PbD consist in theoretical and experimental approaches, and appear far to be ready for everyday implementation in industrial practice [140,141,142,143,144]. In [145] an approach for PbD in industrial welding applications is presented. However, the definition of robot paths is performed by walk-through programming, thus the robot can only imitate demonstrated trajectories.…”

Section: Programming By Demonstrationmentioning

confidence: 99%

“…Moving along these lines, the approaches presented in [122,123,145], which have been discussed above, propose the use of walk-through programming for welding robots. A similar approach has been described also in [16].…”

Section: Weldingmentioning

confidence: 99%

“…-[122,123,145]: walk-through programming for welding robots -[157]: dual arm system taught by hands movements (using a Leap Motion) -[158]: welding path reconstruction by stereo vision ASSEMBLY -[…”

mentioning

confidence: 99%

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Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications

et al. 2018

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Section: Robot Programmingmentioning

confidence: 99%

Section: Programming By Demonstrationmentioning

confidence: 99%

Section: Weldingmentioning

confidence: 99%

mentioning

confidence: 99%

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Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications

et al. 2018

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“…It allows the operator to play the role of an instructor that physically moves the robot through the desired positions within its workspace. Examples of applications that used force guidance for programming are the definition of welding trajectories (Hollmann et al , 2010), the assembly of structures in civil construction (Lee et al , 2007) and the assembly of parts performed in collaboration between a robot and a human (Schraft et al , 2005).…”

Section: Introductionmentioning

confidence: 99%

A comparison of industrial robots interface: force guidance system and teach pendant operation

Rodamilans

Villani

Trabasso

et al. 2016

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Purpose This paper aims to propose an evaluation method to compare two different Human–Robot Interaction (HRI) solutions that can be used for on-line programming in an industrial context: a force guidance system and the traditional teach pendant operation. Design/methodology/approach The method defines three evaluation criteria (agility, accuracy and learning) and describes an experimental approach based on the analysis of variance to verify the performance of guidance systems according to these criteria. This method is used in this paper to compare the traditional teach pendant interface with an implementation of a force guidance system based on the use of an external force/torque sensor. Findings The application of the proposed method to an off-the-shelf industrial robot shows that the force guidance system has a better performance according to the agility criterion. Both solutions have a similar performance for the accuracy criterion, with a limit of about 2 mm in the achieved position accuracy. Regarding the learning criterion, the authors cannot affirm that any of the methods has an improved agility when the operator repeats the tasks. Practical implications This work supports the selection of guidance systems to be used in on-line programming of industrial applications. It shows that the force guidance system is an option potentially faster than the teach pendant when the required positioning accuracy is greater than 2 mm. Originality/value The new method proposed in this paper can be applied to a large range of robots, not being limited to commercial available collaborative robots. Furthermore, the method is appropriate to accomplish further investigations in HRI not only to compare programming methods but also to evaluate guidance systems approaches or robot control systems.

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Common Sensors in Industrial Robots: A Review

Liu

2019

J. Phys.: Conf. Ser.

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The application of industrial robots has greatly promoted the development of industry in the past decades. Now with the proposal and prevalence of Industry 4.0, industrial robots are required to be more independent and intelligent to accomplish more complex and flexible tasks. The advancement of industrial robots relies on the development and progress of multiple technologies, among which sensors are the indispensable part. They can acquire abundant information to help industrial robots implement their functions. This paper reviews the recent literatures and gives a summary and introduction of the commonly used sensors in industrial robots. Additionally, the applications of these sensors in diverse functions of industrial robots are also presented. Finally, the developing direction and challenges of industrial robots in the future are discussed in the last part of this article.

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A HMM-based approach to learning probability models of programming strategies for industrial robots

Cited by 4 publications

References 12 publications

Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications

Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications

A comparison of industrial robots interface: force guidance system and teach pendant operation

Common Sensors in Industrial Robots: A Review

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