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Development of a Voice-controlled Intelligent Wheelchair System using Raspberry Pi

机译:使用覆盆子PI开发语音控制智能轮椅系统

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This paper proposed a voice recognition-based intelligent wheelchair system for physically disabled people who unable to control the wheelchair by their upper and lower limbs. This development employs voice command to controls the movement of the wheelchair in different directions. The android device is used as microphone to be connected to the Google Assistant prior to data processing by the Raspberry Pi. The Raspberry Pi will then command the servo motors to act accordingly. This system offers automatic obstacle detection via the use of an infrared sensor which aids the user to apply momentary brake button upon the obstacle detection. The proposed development has been evaluated in terms of movement accuracy and system responsiveness upon the commands given, in both control mode i.e., voice controller and joystick controller. For the movement accuracy, the results indicate that the minimum accuracies are 90% and 95% for the voice recognition controller and joystick controller, respectively. For the system responsiveness, the system response in less than 1.2 seconds for the voice recognition controller and less than 0.65 seconds for the joystick controller. With this noticeable performance, the intelligent wheelchair enables users with limited control over their limbs to maneuver the wheelchair using voice commands.
机译:本文提出了一种基于语音识别的智能轮椅系统,用于物理残疾人,无法通过上下肢控制轮椅。此开发采用语音命令来控制轮椅在不同方向上的移动。 Android设备用作覆盆子PI数据处理之前要连接到Google助手的麦克风。然后,覆盆子PI将命令伺服电机相应地行动。该系统通过使用红外传感器提供自动障碍物检测,该传感器有助于用户在障碍物检测时施加瞬时制动按钮。在控制模式I.,语音控制器和操纵杆控制器中,在给定的命令时,已经在移动准确性和系统响应方面进行了评估。为了运动精度,结果表明,语音识别控制器和操纵杆控制器的最小精度分别为90%和95%。对于系统响应性,语音识别控制器的系统响应小于1.2秒,对于操纵杆控制器小于0.65秒。凭借这种明显的性能,智能轮椅使用户能够使用肢体的有限控制,使用语音命令操纵轮椅。

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