Kinova Jaco wheelchair robot arm and hand for rehabilitation and assistance to the disabled

机器人手臂和手可以帮助残疾人和老年人完成日常操作任务。电动轮椅在今天很常见，它提供了机动性，从而为那些本来只能呆在家里的人提供了自由和独立。我们的研究旨在让上半身残疾的人有能力过更独立的生活。许多电动轮椅使用者的手臂功能也有所减少。在这里，机械手臂和手可以提供帮助。然而，由于它们有更多的关节和马达，控制起来要比轮椅复杂得多。我们建议研究从运动和力控制到人机界面的问题。该小组的四名副主任横跨三个系：计算机科学、电气工程和康复医学，因此完全有资格承担这项跨学科的研究。为了进行真实的实验，我们需要购买一个安装在轮椅上的机器人手臂和手。Kinova的Jaco机器人特别设计得轻巧细长，可以安装在轮椅的扶手上。目前Jaco的手臂和手是通过轮椅操纵杆控制的。然而，虽然一个2自由度的轮椅操纵杆足以控制轮椅上两个轮式电机的速度和方向，但当用于控制Jaco手臂和手上的7个电机时，它就很麻烦了。为了完成操作任务，用户必须多次切换操纵杆控制的空间方向和旋转。我们的目标是使用视觉和其他传感来简化机器人的控制界面。计算机视觉可以检测物体；一旦用户选择了他们想要抓住的物体，系统就可以计算出这些物体的适当运动轨迹。在这种方法中，可触及的对象将显示在屏幕上，用户只需选择他或她想要操作的对象。然后，机器人手臂可以使用计算的轨迹来执行详细的运动控制，以向选定的物体移动。这极大地简化了用户交互从众多的操纵杆运动和模式切换到一个单一的选择。肌电图（EMG）也为无法使用物理交互设备的其他运动障碍患者提供了控制机器人的潜力。目前Jaco是位置控制的。为了更灵活地与环境相互作用，我们打算研究基于关节扭矩传感器和手臂建模的力控制，而不是基于传统的末端执行器传感器。轮椅臂和手系统是便携式的，将由科学、医学和工程实验室的四个PI共享。我们还将把它带到格伦罗斯康复医院进行患者测试。

Robot arms and hands can potentially help disabled and elderly with daily manipulation tasks. Power wheelchairs are common today and provide mobility, and thus freedom and independence to people who would otherwise be home bound. Our research aims to give upper-body disabled individuals the ability to live a more independent life. Many users of power wheelchairs also have reduced arm function. Here robot arms and hands can help. However, having more joints and motors, these are far more complex to control than the wheelchair. We propose to research from issues in motion and force control to human-robot interfaces. The group of four co-PI span three departments, Computer Science, Electrical Engineering and Rehabilitation Medicine and are thus well qualified to take on this interdisciplinary research. To perform realistic experiments we need to purchase a wheelchair mounted robot arm and and hand. Kinova's Jaco robot is specifically designed to be light and slender so as to mount on the armrest of a wheelchair. Currently the Jaco arm and hand is controlled through the wheelchair joystick. However while a 2Degree-Of-Freedom (DOF) wheelchair joystick is sufficient for controlling the speed and direction of the two wheel motors in a wheelchair, it is cumbersome when used to control the 7 motors in the Jaco arm and hand. The user has to switch which spatial directions and rotations that the joystick controls numerous times in order to complete a manipulation task. Our goal is to use vision and other sensing to simplify the control interface to the robot. Computer vision can detect objects; once the user selects what objects they intend to grasp, the system could then calculate appropriate motion trajectories to these objects. In this approach, reachable objects would be shown on a screen and the user merely selects what object he or she wants to manipulate. The robot arm can then use the calculated trajectory to perform the detailed motion control to move towards the selected object. This greatly simplifies the user interaction from numerous joystick motions and mode switches to a single selection. Electromyography (EMG) provides the potential to control the robot also for individuals with other motor impairments who cannot use a physical interaction device. Currently the Jaco is position controlled. To enable nimbler interactions with the environment we intend to research force control based not on conventional end effector sensors, but on joint torque sensors and arm modeling. The wheelchair arm and hand system is portable and will be shared between the four PI between labs in Science, Medicine, and Engineering. We will also bring it to the Glenrose Rehabilitation hospital for patient tests.