Towards Safe Speed and Separation Monitoring in Human-Robot Collaboration with 3D-Time-of-Flight Cameras

Himmelsbach, Urban B.; Wendt, Thomas M.; Lai, Matthias

doi:10.1109/irc.2018.00042

Cited by 12 publications

(7 citation statements)

References 8 publications

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“…We showed that time-of-flight (ToF) sensors are suitable for this task. The first approaches used a camera mounted on the flange of the robot [17]. Further research investigated the use of single-pixel ToF sensors distributed over the links of the manipulator [18].…”

Section: Introductionmentioning

confidence: 99%

Human–Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human–Robot Collaboration

Himmelsbach

Wendt

Hangst

et al. 2021

Sensors

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Human–robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is often quite low compared to traditional robotic applications without human interaction. Especially for applications that use speed and separation monitoring, there is potential to increase the efficiency with a cost-effective and easy to implement method. In this paper, we proposed to add human–machine differentiation to the speed and separation monitoring in human–robot collaborative applications. The formula for the protective separation distance was extended with a variable for the kind of object that approaches the robot. Different sensors for differentiation of human and non-human objects are presented. Thermal cameras are used to take measurements in a proof of concept. Through differentiation of human and non-human objects, it is possible to decrease the protective separation distance between the robot and the object and therefore increase the overall efficiency of the collaborative application.

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Section: Introductionmentioning

confidence: 99%

Human–Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human–Robot Collaboration

Himmelsbach

Wendt

Hangst

et al. 2021

Sensors

Self Cite

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“…The synchronization interval was set to 1 s. When the synchronized state was achieved, the trigger's position of the synchronizing camera is recorded using an oscilloscope. The necessary buffer is calculated using (2). With t overlap = 0.08 ms from the first…”

Section: Measurements and Resultsmentioning

confidence: 99%

Interference Avoidance for Two Time-of-Flight Cameras Using Autonomous Optical Synchronization

Wermke

Wubbenhorst

Meffert

2020

2020 6th International Conference on Control, Automation and Robotics (ICCAR)

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Time-of-Flight (ToF) cameras acquire 3-D images where each pixel relates to the distance in the observed scene. These images are acquired by emitting modulated light and measuring the phase of its reflection from an object. Improvements in ToF camera technology make it a promising alternative to current 3-D imaging sensors despite possessing comparatively lower resolution. Overcoming lower resolution, of single ToF camera images, is achieved using a multi-camera setup. However, the simultaneous operation of multiple ToF cameras causes interference resulting in erroneous depth measurements. An option to mitigate interference is the arrangement of multiple cameras in a consecutive order sharing the same frequency in assigned time slots, such that each camera illuminates the scene exclusively, a procedure known as time division multiple access (TDMA). The assignment of acquisition times is usually performed by a master synchronizing device implementing a time synchronization protocol that requires an additional communication channel. This paper presents a different approach requiring no additional infrastructure to utilize TDMA by adding a synchronization software procedure to the camera's microprocessor which effectively enables a camera to sense the acquisition process of other cameras and rapidly synchronize itself autonomously to operate without interference. Experimental results with two ToF cameras provide substantive evidence of the efficacy of this approach. The operation of the standalone cameras achieved the desired synchronization without illumination interference. The proposed synchronization procedure takes advantages of the zero interference of TDMA and overcomes traditional hard-wired synchronization setups, offering an autonomous and potentially mobile operation of ToF camera deployment.

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“…In this appendix, first, the stability of the tracking error defined in (3) is investigated under the design of (4). Taking the time derivative of (3) and then substituting (4) yields ė = Vd − Ĵ Ĵ * ( Vd + K p ē) (12) and utilizing (5a) results in…”

Section: Appendix Amentioning

confidence: 99%

Toward safe and high-performance human–robot collaboration via implementation of redundancy and understanding the effects of admittance term parameters

et al. 2021

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Summary Today, demandsin industrial manufacturing mandate humans to work with large-scale industrial robots, and this collaboration may result in dangerous conditions for humans. To deal with this situation, this work proposes a novel approach for redundant large-scale industrial robots. In the proposed approach, an admittance controller is designed to regulate the interaction between the end effector of the robot and the human. Additionally, an obstacle avoidance algorithm is implemented in the null space of the robot to prevent any possible unexpected collision between the human and the links of the robot. After safety performance of this approach is verified via simulations and experimental studies, the effect of the parameters of the admittance controller on the performance of collaboration in terms of both accuracy and total human effort is investigated. This investigation is carried out via 8 experiments by the participation of 10 test subjects in which the effect of different admittance controller parameters such as mass and damper are compared. As a result of this investigation, tuning insights for such parameters are revealed.

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Towards Safe Speed and Separation Monitoring in Human-Robot Collaboration with 3D-Time-of-Flight Cameras

Cited by 12 publications

References 8 publications

Human–Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human–Robot Collaboration

Human–Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human–Robot Collaboration

Interference Avoidance for Two Time-of-Flight Cameras Using Autonomous Optical Synchronization

Toward safe and high-performance human–robot collaboration via implementation of redundancy and understanding the effects of admittance term parameters

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