A project team in the HCI Undergraduate Capstone Project collaborated with researchers in the Personal Robotics Lab to design a new control for a popular assistive robotic arm. It is shown by pilot studies to dramatically cut cognitive demand, frustration, and the level of exerted effort by users.

The team consisted of Whitney Aaronson, Yeon Soo Park, Kevin Schaefer, and Shreepal Shah. They spent the semester with working with Laura Herlant, Dr. Tekin Mericli, and Professor Siddhartha Srinivasa of the Robotics Institute’s Personal Robotics Lab.

The robotic arm, MICO by Kinova Robotics, is an innovative wheelchair-mounted robotic manipulator arm with a two-fingered hand intended for people with paraplegia. The team found that its current control mechanisms are severely lacking in usability and learnability, finding it “mentally exhausting” to perform even simple tasks.

The team began by creating a simple experiment to evaluate people’s experiences and preferences in controlling a robotic arm through both manual, low-level movements (like “move left”, “move down”, etc) and high-level, automated movements  (like “pick up the bottle”). Their findings demonstrated that most people preferred the use of automated movements because of the ability to focus less on the task of controlling the arm.

The redesigned control is based primarily on a recording feature, that allows users of the arm to record repetitive movements and replay them using the joystick already built into in their wheelchair. It was designed in such a way to allow users to feel in control as well as capable of making adjustments to the recordings as they are played back.

Two early pilot studies suggest that the redesigned control offers significant benefits in certain situations. One study participant said “It was definitely easier to use the recording. The [current control] was difficult to use in comparison”, a sentiment shared by many of the participants.