Practical application of a safe human-robot interaction software - Bingol, Mustafa Can; Aydogmus, Omur (Emerald Group Publishing Ltd, 2020)
Purpose Because of the increased use of robots in the industry, it has become inevitable for humans and robots to be able to work together. Therefore, human security has become the primary noncompromising factor of joint human and robot operations. For this reason, the purpose of this study was to develop a safe human-robot interaction software based on vision and touch. Design/methodology/approach The software consists of three modules. Firstly, the vision module has two tasks: to determine whether there is a human presence and to measure the distance between the robot and the human within the robot's working space using convolutional neural networks (CNNs) and depth sensors. Secondly, the touch detection module perceives whether or not a human physically touches the robot within the same work environment using robot axis torques, wavelet packet decomposition algorithm and CNN. Lastly, the robot's operating speed is adjusted according to hazard levels came from vision and touch module using the robot's control module. Findings The developed software was tested with an industrial robot manipulator and successful results were obtained with minimal error. Originality/value In this study, a new and practical safety algorithm is proposed and the health of people working with industrial robots is guaranteed.
Keywords: Safety; Artificial intelligence; Autonomous robots; Convolutional neural network; Human-robot interaction