Abstract
Robot arms are one of many assistive technologies used by people with motor impairments. Assistive robot arms can allow people to perform activities of daily living (ADL) involving grasping and manipulating objects in their environment without the assistance of caregivers. Suitable input devices (e.g., joysticks) mostly have two Degrees of Freedom (DoF), while most assistive robot arms have six or more. This results in time-consuming and cognitively demanding mode switches to change the mapping of DoFs to control the robot. One option to decrease the difficulty of controlling a high-DoF assistive robot arm using a low-DoF input device is to assign different combinations of movement-DoFs to the device’s input DoFs depending on the current situation (adaptive control). To explore this method of control, we designed two adaptive control methods for a realistic virtual 3D environment. We evaluated our methods against a commonly used non-adaptive control method that requires the user to switch controls manually. This was conducted in a simulated remote study that used Virtual Reality and involved 39 non-disabled participants. Our results show that the number of mode switches necessary to complete a simple pick-and-place task decreases significantly when using an adaptive control type. In contrast, the task completion time and workload stay the same. A thematic analysis of qualitative feedback of our participants suggests that a longer period of training could further improve the performance of adaptive control methods.
Highlights
Publisher’s Note: MDPI stays neutralRobotic solutions are becoming increasingly prevalent in many areas of our professional and personal lives and have started to evolve into collaborators [1,2]
Heeding the call for more flexible interfaces, we proposed in our recent work an adaptive control concept for assistive robot arms that promises to allow users to be in control at all times while still providing them with more assistance during activities of daily living (ADL) than the standard mode switch control concept [6]
We proposed a representation of these assignments of input eachDoFs column represents the of an similar input device
Summary
Publisher’s Note: MDPI stays neutralRobotic solutions are becoming increasingly prevalent in many areas of our professional and personal lives and have started to evolve into collaborators [1,2]. While a near-complete integration into professional and social life is the final goal, current assistive robotic technologies focus on performing activities of daily living (ADLs) These include tasks ranging from essentials such as eating and drinking to more complex behaviors such as grooming and activities associated with leisure time [4]. A robotic arm with a simple gripper can freely operate in 3D space and move along Cartesian space as well as yaw, pitch, and rotate This typically results in five to seven DoFs. This typically results in five to seven DoFs Standard input devices, such as joysticks, only cover two DoFs. To control a high-DoF device with a low-DoF input device, mode switching is used. This means that at any point in time, the user has to select with regard to jurisdictional claims in published maps and institutional affiliations
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