LoCAR – Low-Cost Autonomous Robot for Object Detection with Voice Command and MobileNets

ABSTRACT

This work details the design, construction, implementation and testing of a standalone robot, based on a convolutional neural network, which receives a voice command, searches and recognizes the target through its camera and moves to the object or person properly recognized. The success rate for the recognition stage has reached 82% in the median for objects tested, 100% for chairs, bottles and people. The processing was performed on a Raspberry Pi 3 B board integrated with an Arduino UNO to control the actuators.

Acknowledgments

Credit to Abner F. Bertelline, Alesia N. B. Melo, Felipe J. L. Rita and Leonardo M. Tozato for developing the initial version of the LoCAR robot.

Notes

1. https://www.arduino.cc/

2. https://www.raspberrypi.org/