Doctor of Philosophy

dissertationHumans generally have difficulty performing precision tasks with their unsupported hands. To compensate for this difficulty, people often seek to support or rest their hand and arm on a fixed surface. However, when the precision task needs to be performed over a workspace larger than what can be reached from a fixed position, a fixed support is no longer useful. This dissertation describes the development of the Active Handrest, a device that expands its user's dexterous workspace by providing ergonomic support and precise repositioning motions over a large workspace. The prototype Active Handrest is a planar computer-controlled support for the user's hand and arm. The device can be controlled through force input from the user, position input from a grasped tool, or a combination of inputs. The control algorithm of the Active Handrest converts the input(s) into device motions through admittance control where the device's desired velocity is calculated proportionally to the input force or its equivalent. A robotic 2-axis admittance device was constructed as the initial Planar Active Handrest, or PAHR, prototype. Experiments were conducted to optimize the device's control input strategies. Large workspace shape tracing experiments were used to compare the PAHR to unsupported, fixed support, and passive moveable support conditions. The Active Handrest was found to reduce task error and provide better speedaccuracy performance. Next, virtual fixture strategies were explored for the device. From the options considered, a virtual spring fixture strategy was chosen based on its effectiveness. An experiment was conducted to compare the PAHR with its virtual fixture strategy to traditional virtual fixture techniques for a grasped stylus. Virtual fixtures implemented on the Active Handrest were found to be as effective as fixtures implemented on a grasped tool. Finally, a higher degree-of-freedom Enhanced Planar Active Handrest, or E-PAHR, was constructed to provide support for large workspace precision tasks while more closely following the planar motions of the human arm. Experiments were conducted to investigate appropriate control strategies and device utility. The E-PAHR was found to provide a skill level equal to that of the PAHR with reduced user force input and lower perceived exertion

Doctor of Philosophy

dissertationMost humans have difficulty performing precision tasks, such as writing and painting, without additional physical support(s) to help steady or offload their arm's weight. To alleviate this problem, various passive and active devices have been developed. However, such devices often have a small workspace and lack scalable gravity compensation throughout the workspace and/or diversity in their applications. This dissertation describes the development of a Spatial Active Handrest (SAHR), a large-workspace manipulation aid, to offload the weight of the user's arm and increase user's accuracy over a large three-dimensional workspace. This device has four degrees-of-freedom and allows the user to perform dexterous tasks within a large workspace that matches the workspace of a human arm when performing daily tasks. Users can move this device to a desired position and orientation using force or position inputs, or a combination of both. The SAHR converts the given input(s) to desired velocit

Master of Science

thesisAdmittance-type robotic devices are commonly used to complete tasks that require a high degree of precision and accuracy because they appear nonbackdrivable to many disturbances from the environment. Admittance-type robots are controlled using admittance control; a human interacts directly with a force sensor mounted to the robot, and the robot is computer-controlled to move in response to the applied force. The experiment herein was conducted to determine under which operating conditions human velocity control is optimized for admittance devices that are controlled under proportional-velocity control, and to determine the degradation in control under nonoptimal conditions. In this study, the desired velocity of the device was shown on a visual display. The desired velocity was shown with a scaling factor from the actual velocity of the device because the device often moved at velocities too slow to perceive visually. The admittance gain, ka, desired velocity, Vd, and the visualization scale factor, S were tuned to adjust the user's experience when interacting with an admittance device. We found that in velocity-tracking tasks, scaling the visual feedback only has a significant effect on performance for very slow desired velocities (0.1mm/s), for the range of velocities tested here. In this thesis, we give evidence that there exists a range of velocities and forces within which humans optimally interact with admittance-type devices. We found that the optimal range of velocities is between 0.4mm/s and 1.0mm/s, inclusive, and the optimal range of forces is between 0.4 N and 4.0 N, inclusive. To ensure optimal velocity-control performance, the admittance gain should be selected such that the desired velocity and target force remain within their respective optimal ranges simultaneously. We also found that on average subjects moved faster than the desired velocity when the desired velocity was 0.1 mm/s and subjects were slower than the desired velocity when it was higher than 0.4 mm/s. For each admittance gain there is a different threshold velocity at which velocity-control accuracy is optimal in the aggregate. If the device operates at a velocity that is faster or slower than the threshold velocity the operator will tend to lag or lead the desired velocity, respectively