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.

中文翻译：

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LoCAR – 使用语音命令和 MobileNets 进行物体检测的低成本自主机器人

摘要 这项工作详细介绍了基于卷积神经网络的独立机器人的设计、构造、实施和测试，该机器人接收语音命令，通过其摄像头搜索和识别目标，然后移动到正确识别的物体或人。识别阶段的成功率在测试对象的中位数中达到了 82%，椅子、瓶子和人的成功率达到了 100%。处理是在与 Arduino UNO 集成的 Raspberry Pi 3 B 板上执行的，以控制执行器。