Faculty of Engineering & Technology, Philadelphia University, Amman 19392, Jordan.
Sensors (Basel). 2020 May 19;20(10):2872. doi: 10.3390/s20102872.
Autonomous wheelchairs are important tools to enhance the mobility of people with disabilities. Advances in computer and wireless communication technologies have contributed to the provision of smart wheelchairs to suit the needs of the disabled person. This research paper presents the design and implementation of a voice controlled electric wheelchair. This design is based on voice recognition algorithms to classify the required commands to drive the wheelchair. An adaptive neuro-fuzzy controller has been used to generate the required real-time control signals for actuating motors of the wheelchair. This controller depends on real data received from obstacle avoidance sensors and a voice recognition classifier. The wheelchair is considered as a node in a wireless sensor network in order to track the position of the wheelchair and for supervisory control. The simulated and running experiments demonstrate that, by combining the concepts of soft-computing and mechatronics, the implemented wheelchair has become more sophisticated and gives people more mobility.
自主轮椅是增强残疾人士行动能力的重要工具。计算机和无线通信技术的进步促进了智能轮椅的提供，以满足残疾人的需求。本研究论文介绍了语音控制电动轮椅的设计和实现。该设计基于语音识别算法来对所需命令进行分类，以驱动轮椅。自适应神经模糊控制器已用于生成用于驱动轮椅电机的所需实时控制信号。该控制器依赖于来自避障传感器和语音识别分类器的实际数据。轮椅被视为无线传感器网络中的一个节点，以便跟踪轮椅的位置和进行监督控制。模拟和运行实验表明，通过将软计算和机电一体化的概念相结合，所实现的轮椅变得更加复杂，为人们提供了更多的行动能力。
