Ryan Coulson1, 2, Max Kirkpatrick1, 3, Megan Robinson1, 4, Meghan Donahue5, Devin R. Berg1 1Engineering & Technology Department, University of Wisconsin-Stout; 2Department of Mechanical Engineering, Lafayette College; 3Department of Mechanical Engineering, University of South Carolina; 4Department of Electrical Engineering and Computer Science, Case Western Reserve University; 5Stout Vocational Rehabilitation Institute, University of Wisconsin-Stout User Testing of a Continuum Manipulator for Assistive Technology User No. Average Completion Time (s) – Session One Average Completion Time (s) – Session Two Average Completion Time (s) – Session Three Percent Improvement 1 115.18 121.79 58.84 48.91 2 121.79 112.57 66.02 42.96 3 170.65 149.66 120.40 29.45 User No. Average Completion Time (s) – Session One Average Completion Time (s) – Session Two Percent Improvement 1 235.14 168.18 28.47 2 234.57 214.89 8.39 3 435.57 288.30 33.81 Control Scheme Avg Completion Time (s) Standard Deviation (s) Average Intuition Ranking Single-Joystick Compensative 63.00 54.61 1.86 Dual-Joystick 72.76 42.60 1.93 Single-Joystick Segmented 96.20 55.58 2.21 The use of robots in assistive technology is well-studied, with numerous robotic arms for rehabilitative applications that have been designed and tested to-date, and several that are commercially available [1, 2, 3]. These robots are intended to improve independence and quality of life for people who are unable to perform activities of daily living (ADLs) without additional aid. Unfortunately, they are often prohibitively expensive, costing tens of thousands of dollars [4]. Additionally, they pose a risk of harmful collision to their users and must incorporate sophisticated sensors and control methods to ensure the users’ safety. This work evaluates an alternative platform for assistive robotics which alleviates these issues: continuum manipulators. Continuum manipulators are robots that lack rigid segments and discrete joints [5]. Instead, they function by bending continuously along their length, like the trunk of an elephant or the tentacle of an octopus. The use of continuum manipulators in assistive technology has been proposed with respect to the ADL of bathing by Ansari et al., 2017 [6], although no user testing of this proposal has been completed. This work is supported by the National Science Foundation under Grant No. CNS-1560219. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. Table 1. Results from Round One of user testing for n = 14 users. References [1] Chung, C. S., Wang, H., & Cooper, R. A. (2013). DOI: 10.1179/2045772313Y.0000000132 [2] Driessen, B. J. F., Evers, H. G., & v Woerden, J. A. (2001). DOI: 10.1243/0954411011535876 [3] Maheu, V., Archambault, P. S., Frappier, J., & Routhier, F. (2011). DOI: 10.1109/ICORR.2011.5975397 [4] Allin, S., Eckel, E., Markham, H., & Brewer, B. R. (2010). DOI: 10.1016/j.pmr.2009.09.001 [5] Walker, I. D. (2013). DOI: 10.5402/2013/726506 [6] Ansari, Y., Manti, M., Falotico, E., Mollard, Y., Cianchetti, M., & Laschi, C. (2017). DOI: 10.1177/1729881416687132 Table 2. Results from Round Two of user testing: Peg-in-hole task. Table 3. Results from Round Two of user testing: Drawer task. Table 1 shows the results from Round One of user testing. On average, users were able to complete the given task most quickly using Compensative control, followed by Dual control and then Segmented control. The standard deviations for these data are relatively large, as users demonstrated a wide range of skill levels when using the robot. Examining the average intuition rankings, it can be seen that users rated Compensative control as most intuitive, followed by Dual control and then Segmented control. This result further supports Compensative control as the superior of the three control schemes. Tables 2 and 3 show results from Round Two