Tool delivery robot using convolutional neural network

Javier Pinzon-Arenas, Robinson Jimenez-Moreno


In the following article, it is presented a human-robot interaction system where algorithms were developed to control the movement of a manipulator in order to allow it to search and deliver, in the hand of the user, a desired tool with a certain orientation. A Convolutional Neural Network (CNN) was used to detect and recognize the user's hand, geometric analysis for the adjustment of the delivery status of the tool from any position of the robot and any orientation of the gripper, and a trajectory planning algorithm for the movement of the manipulator. It was possible to use the activations of a CNN developed in previous works for the detection of the position and orientation of the hand in the workspace and thus track it in real time, both in a simulated environment and in a real environment.


Convolutional neural network; Hand tracking; Human-robot interaction; Path planning

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578