Semi-Autonomous Tongue Control of an Assistive Robotic Arm for Individuals with Quadriplegia

Hildebrand, Max; Bonde, Frederik; Kobborg, Rasmus Vedel Nonboe; Andersen, Christian; Norman, Andreas; Thøgersen, Mikkel; Bengtson, Stefan Hein; Došen, Strahinja; Struijk, N. S. Lotte Andreasen

doi:10.1109/icorr.2019.8779457

Cited by 8 publications

(10 citation statements)

References 19 publications

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“…The tool frame based control allowed the user to look around using the camera attached on the end-effector and reach directly towards the desired object to pick it up. Hildebrand et al [28] showed that the tool frame control decreased the TCT and path efficiency compared with the base frame when solving a simple pick and place task. However, as mentioned by Campeau-Lecours et al [30], tool-frame control can be difficult to understand and this is especially true when controlling through a stationary 2D visual feedback as was provided by the camera at the headrest of the wheelchair in this experiment.…”

Section: B Layout Differencementioning

confidence: 99%

“…In an attempt to develop a more intuitive low-level control scheme, Campeau-Lecours et al [30] proposed orientation control, which is based on a newly defined adaptive reference frame. Another attempt to provide a better performance when low-level controlling an ARM is endeffector control in which both the robot translation and rotation are defined according to the orientation of the end-effector [28]. As indicated by these studies, other low-level control methods have the potential to make the robotic control even more intuitive for disabled users.…”

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confidence: 99%

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A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

et al. 2022

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It is crucial to increase the independence of severely disabled individuals. Assistive robotics can aid in the desired activities of daily living, including tasks requiring remote performance e.g. grasping remote objects, turning switches on/off, and opening/closing doors. The robot control is compromised by the lack of efficient interfaces for individuals with disabilities and the lack of depth perception. This paper addresses these challenges by presenting the development and evaluation of efficient tongue-based robot interfaces and low-level robot control schemes targeting telerobotic control through a 2D display. Ten able-bodied participants were successful in completing ten rounds of controlling a JACO robot to perform a pouring water task, using five different control methods, under 2D or 3D visual feedback. The tool-frame based tongue interface layout, L2_TF (with emulated joystick, mode switch button and a "GO" button) improved the 2D visual guided control of the JACO robot compared with the other tongue control methods. The mean trajectory length of completing the task using L2_TF was 3% longer compared with the standard joystick when controlling through 2D. The trajectory length for reaching and grabbing a bottle was shortest for L2_TF compared with all other control methods, including the joystick. The iTongue control layouts performed well in gripping time, showing no significant difference between 2D and 3D. The transition from 2D to 3D resulted in a mean decrease of 27.7% for task completion time across all interfaces. L2_TF and the joystick had the strongest and most similar robustness to the transition between 3D and 2D.

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Section: B Layout Differencementioning

confidence: 99%

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confidence: 99%

A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

et al. 2022

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“…A semi-autonomous control scheme, where parts of the control are automated using computer vision, is included in the system to further enhance the tongue-based control of the exoskeleton. Several studies have reported increased performance when employing computer vision for semi-autonomous control of assistive robotic manipulators [10], such as completing tasks faster [18,19] or being more precise in the movement of the manipulator [20,21]. Furthermore, there are several examples of computer vision either improving the fine control of an upper limb exoskeleton [13,21] or automating entire parts of a task [11,22,23] for users with paralysis.…”

Section: Related Workmentioning

confidence: 99%

“…Many of the approaches relying on computer vision employ a clear-cut strategy for arbitrating control between the user and the system, where certain parts of the process are completely automated [10]. For example, reaching for and grasping an object once the user triggers this predefined task, either from a tongue-based interface [20], through voice commands [18], or through eye movements [11,22]. The user would, in these cases, relinquish complete control until the task is completed, i.e., the object is reached and grasped.…”

Section: Related Workmentioning

confidence: 99%

Computer Vision-Based Adaptive Semi-Autonomous Control of an Upper Limb Exoskeleton for Individuals with Tetraplegia

et al. 2022

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We propose the use of computer vision for adaptive semi-autonomous control of an upper limb exoskeleton for assisting users with severe tetraplegia to increase independence and quality of life. A tongue-based interface was used together with the semi-autonomous control such that individuals with complete tetraplegia were able to use it despite being paralyzed from the neck down. The semi-autonomous control uses computer vision to detect nearby objects and estimate how to grasp them to assist the user in controlling the exoskeleton. Three control schemes were tested: non-autonomous (i.e., manual control using the tongue) control, semi-autonomous control with a fixed level of autonomy, and a semi-autonomous control with a confidence-based adaptive level of autonomy. Studies on experimental participants with and without tetraplegia were carried out. The control schemes were evaluated both in terms of their performance, such as the time and number of commands needed to complete a given task, as well as ratings from the users. The studies showed a clear and significant improvement in both performance and user ratings when using either of the semi-autonomous control schemes. The adaptive semi-autonomous control outperformed the fixed version in some scenarios, namely, in the more complex tasks and with users with more training in using the system.

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“…One such system is the inductive tongue control interface (ITCI) proposed in [17], which has 18 available sensors and is therefore suitable for control of a high DOF system such as an ARM. The ITCI has been used in several studies to control a six DOF ARM [5], [20]- [22], one of which in a remote setting [21], demonstrating the potential of the solution to improving the quality of life and level of independence of individuals with tetraplegia. However, in all of the studies the accuracy of task completion, both in terms of time and success rate, could potentially be improved by the integration of semi-autonomous assistance when controlling the robot.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Semi-automatic Robot Control by Tongue in a Remote Setting for Individuals with Tetraplegia

Mortensen

Pedersen

Knudsen

et al. 2021

2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)

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Semi-Autonomous Tongue Control of an Assistive Robotic Arm for Individuals with Quadriplegia

Cited by 8 publications

References 19 publications

A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

A Dedicated Tool Frame Based Tongue Interface Layout Improves 2D Visual Guided Control of an Assistive Robotic Manipulator: A Design Parameter for Tele-Applications

Computer Vision-Based Adaptive Semi-Autonomous Control of an Upper Limb Exoskeleton for Individuals with Tetraplegia

Adaptive Semi-automatic Robot Control by Tongue in a Remote Setting for Individuals with Tetraplegia

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