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.
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.
The developed software was tested with an industrial robot manipulator and successful results were obtained with minimal error.
The success of the developed algorithm was demonstrated in the current study and the algorithm can be used in other industrial robots for safety.
In this study, a new and practical safety algorithm is proposed and the health of people working with industrial robots is guaranteed.
Information note: This study was performed at Firat University within the scope of the doctoral thesis titled “The Development of an Artificial Intelligence-Based Self-Programmable Robot Software Using Human-Robot Interaction.”
Bingol, M. and Aydogmus, O. (2020), "Practical application of a safe human-robot interaction software", Industrial Robot: the international journal of robotics research and application, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IR-09-2019-0180Download as .RIS
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