Safe collaboration of humans and SCARA robots

Shariatee, Morteza; Khosravi, Hooman; Fazl-Ersi, Ehsan

doi:10.1109/icrom.2016.7886809

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…Various other works have been carried out during the past decade toward making industrial robots safe enough to work in close collaboration with a human worker. Shariatee et al (2016) used the Kinect sensor as input device to monitor the distance between the human worker and a SCARA robot and a consequent appropriate action by the robot based on the estimated distance. Long et al (2018) studied the use of laser scanners to position the operator in the workspace and Corrales et al (2012) experimented with an inertial motion capture suit to localize the whole body of the human working in collaboration to a robot, still with the objective of finding the distance between the human worker and the robot and a consequent decision-making leading to proper reactions of the robot.…”

Section: Introductionmentioning

confidence: 99%

A neural network based monitoring system for safety in shared work-space human-robot collaboration

Rajnathsing

2018

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Purpose Human–robot collaboration (HRC) is on the rise in a bid for improved flexibility in production cells. In the context of overlapping workspace between a human operator and an industrial robot, the major cause for concern rests on the safety of the former. Design/methodology/approach In light of recent advances and trends, this paper proposes to implement a monitoring system for the shared workspace HRC, which supplements the robot, to locate the human operator and to ensure that at all times a minimum safe distance is respected by the robot with respect to its human partner. The monitoring system consists of four neural networks, namely, an object detector, two neural networks responsible for assessing the detections and a simple, custom speech recognizer. Findings It was observed that with due consideration of the production cell, it is possible to create excellent data sets which result in promising performances of the neural networks. Each neural network can be further improved by using its mistakes as examples thrown back in the data set. Thus, the whole monitoring system can achieve a reliable performance. Practical implications Success of the proposed framework may lead to any industrial robot being suitable for use in HRC. Originality/value This paper proposes a system comprising neural networks in most part, and it looks at a digital representation of the workspace from a different angle. The exclusive use of neural networks is seen as an attempt to propose a system which can be relatively easily deployed in industrial settings as neural networks can be fine-tuned for adjustments.

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Section: Introductionmentioning

confidence: 99%