An Investigation of Security Approaches in Industrial Robots

Bai, Yuchuan; Lei, Qujiang; Zhang, Hongda; Yang, Yang; He, Yue; Duan, Zhongxing

doi:10.1109/iccar.2019.8813393

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…A review of the main safety systems that have been proposed and applied in industrial robotic environments and proven to contribute to the achievement of safe HRC work is given in [6] and in [7]. Literature review regarding the use of vision systems in HRC safety [8] shows that they can be classified into four categories: a) systems that compute the distance between several points and moving obstacles, for example between robotic joints and a human utilizing a depth camera, b) collision avoidance systems, c) human intent detection systems and d) systems that use visualization and monitoring of safety zones created by projecting virtual optical barriers with lasers or projectors.…”

Section: Related Workmentioning

confidence: 99%

“…Fig. 1: Reconfigurable HRC workplace is composed of the: Single Camera Stereo Vision system (SCSV) (2) which is used for close view visual monitoring of assembly space (7); posture monitoring vision system (3) of the workspace (8); safe locations for hands (6); robot (4); computer display (5) and the pickup holder (1). Fig.…”

Section: Visual Quality and Safety Monitoring Systemmentioning

confidence: 99%

See 1 more Smart Citation

Visual quality and safety monitoring system for human-robot cooperation

Kozamernik¹,

Zaletelj²,

Košir³

et al. 2023

Preprint

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Efficient workspace awareness is critical for improved interaction in cooperative and collaborative robotics applications. In addition to safety and control aspects, quality-related tasks such as the monitoring of manual activities and the final quality assessment of the results are also required. In this context, a visual quality and safety monitoring system is developed and evaluated. The system integrates close-up observation of manual activities and posture monitoring. A compact single-camera stereo vision system and a time-of-flight depth camera are used to minimize the interference of the sensors with the operator and the workplace. Data processing is based on a deep learning to detect classes related to quality and safety aspects. The operation of the system is evaluated while monitoring a human-robot manual assembly task. The results show that the proposed system ensures a high level of safety, provides reliable visual feedback to the operator on errors in the assembly process, and inspects the finished assembly with a low critical error rate.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Visual Quality and Safety Monitoring Systemmentioning

confidence: 99%

Visual quality and safety monitoring system for human-robot cooperation

Kozamernik¹,

Zaletelj²,

Košir³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Visual quality and safety monitoring system for human-robot cooperation

Kozamernik

Zaletelj

Košir

et al. 2023

Int J Adv Manuf Technol

View full text Add to dashboard Cite

Efficient workspace awareness is critical for improved interaction in cooperative and collaborative robotic applications. In addition to safety and control aspects, quality-related tasks such as the monitoring of manual activities and the final quality assessment of the results are also required. In this context, a visual quality and safety monitoring system is developed and evaluated. The system integrates close-up observation of manual activities and posture monitoring. A compact single-camera stereo vision system and a time-of-flight depth camera are used to minimize the interference of the sensors with the operator and the workplace. Data processing is based on a deep learning to detect classes related to quality and safety aspects. The operation of the system is evaluated while monitoring a human-robot manual assembly task. The results show that the system ensures a high level of safety, provides reliable visual feedback to the operator on errors in the assembly process, and inspects the finished assembly with a low critical error rate.

show abstract