A Brain Robot Interface For Autonomous Activities Of Daily Living Tasks PDF Download

We have designed and implemented a novel human-robot teleoperation interface based on an intuitive reference frame and hybrid inverse kinematics to perform activities of daily living(ADL) using multiple input devices. Persons with disabilities often rely on caregivers or family members to assist in their daily living activities. Providing robotic assistants with easy and intuitive user interfaces to assist with ADL can improve their quality of life and lift some of the burdens on caregivers and family members. Current human-robot interface solutions, such as joysticks, Kinect based gesture recognition, and touchscreen-based solutions, including smartphones, are still far from being able to operate in an intuitive way when used for complex activities of daily living. In this dissertation, we review the current popular human-robot interfaces and discuss their advantages and disadvantages. When developing our new interface system, we try to maximize as many advantages as possible while minimizing the disadvantages. In this era of smartphones that are packed with sensors, such as accelerometers, gyroscopes, and a precise touch screen, teleoperation control can be interfaced with smartphones to capture the user's intended operation of the robot assistant. We developed three novel human-robot smartphone-based interfaces to operate a robotic arm for assisting persons with disabilities in their ADL tasks. Useful smartphone data, including 3-dimensional orientation and 2-dimensional touchscreen positions, are used as control variables to the robot motion in Cartesian teleoperation. The developed interfaces provide intuitiveness, low cost, and environmental adaptability. Not only the interface devices affect the intuitiveness of the robotic arm teleoperation, but also the inverse kinematics algorithm of the robotic arm is crucial to the whole system intuitiveness as well. The two commonly used reference frames are the Ground and the End-effector reference frames, which do not always provide intuitive control from the perspective of human operators. We conducted preliminary testing in Ground and End-effector reference frames separately to maneuver objects in 3D space. Based on their feedback, we found how users wanted the robot to move and developed a new Intuitive Reference Frame with a novel hybrid inverse kinematics solution(the Hybrid system). This system provides a more natural and easier to use human-robot interface. Two conventional control reference frames(the Ground and the End-effector) are compared with our novel Intuitive control reference frame. An activity of daily living(ADL) task was used to test the performances of the three control reference frames. A 6-D spacemouse, Xbox controller, Omni and a smartphone were used as input devices for the human-robot interfaces to control a Baxter robotic arm and perform the same ADL task using the three different control reference frames. We tested the three control reference frame systems with human subjects and collected qualitative and quantitative data. The results show that overall our Intuitive robotic arm control reference frame with the hybrid inverse kinematics greatly reduced the time and effort needed to manipulate the robotic arm. The results also show that our Hybrid system improved the performances and intuitiveness for all tested input devices.