Detection of Human-Robot Collision using Kinetic

Mathé, Ladislao; Caverzasi, Agustín; Saravia, Fernando; Loreto, G.; Pedroni, Juan Pablo

doi:10.1109/tla.2013.6502793

Cited by 5 publications

(1 citation statement)

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“…These cameras have the characteristics of small overall size, strong environmental perception, image acquisition accuracy, and low price. Mathé et al [3] determined the position between the surgeon and the robot through Kinect to prevent the robot from interfering with the doctor's work. Tupper and Green [4] used RealSense combined with the Mask R-CNN [5] algorithm to determine the relative position relationship between pedestrians and cameras to realize pedestrian proximity detection.…”

Section: Introductionmentioning

confidence: 99%

Human Position Detection Based on Depth Camera Image Information in Mechanical Safety

Zhou

Ren

Zhang

et al. 2022

Advances in Mathematical Physics

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The devices used for human position detection in mechanical safety mainly include safety light curtain, safety laser scanner, safety pad, and vision system. However, these devices may be bypassed when used, and human or equipment cannot be distinguished. To solve this problem, a depth camera is proposed as a human position detection device in mechanical safety. The process of human position detection based on depth camera image information is given; it mainly includes image information acquisition, human presence detection, and distance measurement. Meanwhile, a human position detection method based on Intel RealSense depth camera and MobileNet-SSD algorithm is proposed and applied to robot safety protection. The result shows that the image information collected by the depth camera can detect the human position in real time, which can replace the existing mechanical safety human position detection device. At the same time, the depth camera can detect only human but not mobile devices and realize the separation and early warning of people and mobile devices.

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Section: Introductionmentioning

confidence: 99%