Electric wheelchair-mounted robotic arms can help patients with disabilities to perform their activities in daily living (ADL). Joysticks or keypads are commonly used as the operating interface of Wheelchair-mounted robotic arms. Under different scenarios, some patients with upper limb disabilities such as finger contracture cannot operate such interfaces smoothly. Recently, manual interfaces for different symptoms to operate the wheelchair-mounted robotic arms are being developed. However, the stop the wheelchairs in an appropriate position for the robotic arm grasping task is still not easy. To reduce the individual’s burden in operating wheelchair in narrow spaces and to ensure that the chair always stops within the working range of a robotic arm, we propose here an operating system for an electric wheelchair that can automatically drive itself to within the working range of a robotic arm by capturing the position of an AR marker via a chair-mounted camera. Meanwhile, the system includes an error correction model to correct the wheelchair’s moving error. Finally, we demonstrate the effectiveness of the proposed system by running the wheelchair and simulating the robotic arm through several courses.
In recent years, robot arms are being developed for self-reliance supporting for those who are unable to move without using an electric wheelchair or live a bedridden life. For example, mounting a robot arm on an electric wheelchair or bedside could help the limb disabled people to perform daily activities without nursing. However, the existing robot arms are mainly using traditional operation interfaces like keyboards or joysticks. Under different scenarios, some patients with upper limb disabilities such as contracture cannot operate such interfaces smoothly. In this study, in order to reduce the difficulty in operating robot arms, we developed a new kind of operation system using smartphone touchscreen as screen joystick operating interface. Meanwhile, the system includes a filter which detects and adjusts maloperation due to the capacitive touchscreen panel with high maloperation rate. Finally, an operating test was conducted by a patient with upper limb disabilities, and the effectiveness of this study was shown from the evaluation of the trajectory of robot hands from the initial position to the aim position. In the future, we are planning to develop an innovate operation system for a robot arm which is mounted on the wheelchair, with the effectiveness confirm by several operation tests.
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