Performing Complex Tasks by Users With Upper-Extremity Disabilities Using a 6-DOF Robotic Arm: A Study

Development and evaluation of demonstration information recording approach for wheelchair mounted robotic arm

To offer simple and convenient assistance for the elderly and disabled, researchers focus on programming by demonstration approach to improve the intelligence and adaptability of wheelchair mounted robotic arm assistive robot. But how to easily and quickly obtain the demonstration information is still an urgent problem to be solved. Based on the systematic analysis of the daily living tasks in need of robot assistance, this paper proposes the key-point-based programming by demonstration recording approach to quickly obtain the demonstration information and develops a specified demonstration interface to simplify the operation process. A corresponding evaluation approach is also proposed from the demonstration trajectories and demonstration process two aspects. Additionally, tasks of “holding water glass task”, “eating task”, and “opening door task” are carried out and experimental results, as well as comparative evaluations confirm the validity of the proposed approach with high efficiency. This study can not only offer a convenient and feasible way to obtain the demonstration information of daily living tasks, but also lay a good foundation for the assistive robot to learn relative motion skills, especially for the demonstrated dexterous manipulation skills, and semi-autonomously accomplish complex, multi-step tasks following the user’s instructions in the daily home environment.

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

Robotic assistance via motorized robotic arm manipulators can be of valuable assistance to individuals with upper-limb motor disabilities. Brain-computer interfaces (BCI) offer an intuitive means to control such assistive robotic manipulators. However, BCI performance may vary due to the non-stationary nature of the electroencephalogram (EEG) signals. It, hence, cannot be used safely for controlling tasks where errors may be detrimental to the user. Avoiding obstacles is one such task. As there exist many techniques to avoid obstacles in robotics, we propose to give the control to the robot to avoid obstacles and to leave to the user the choice of the robot behavior to do so a matter of personal preference as some users may be more daring while others more careful. We enable the users to train the robot controller to adapt its way to approach obstacles relying on BCI that detects error-related potentials (ErrP), indicative of the user’s error expectation of the robot’s current strategy to meet their preferences. Gaussian process-based inverse reinforcement learning, in combination with the ErrP-BCI, infers the user’s preference and updates the obstacle avoidance controller so as to generate personalized robot trajectories. We validate the approach in experiments with thirteen able-bodied subjects using a robotic arm that picks up, places and avoids real-life objects. Results show that the algorithm can learn user’s preference and adapt the robot behavior rapidly using less than five demonstrations not necessarily optimal.

Teaching an assistive robotic manipulator to move objects in a cluttered table requires demonstrations from expert operators, but what if the experts are individuals with motor disabilities? Batzianoulis et al. propose a learning approach which combines robot autonomy and a brain-computer interfacing that decodes whether the generated trajectories meet the user’s criteria, and show how their system enables the robot to learn individual user’s preferred behaviors using less than five demonstrations that are not necessarily optimal.

Algorithm to Generate Trajectories in a Robotic Arm Using an LCD Touch Screen to Help Physically Disabled People

In the last two-decade, robotics has attracted a lot of attention from the biomedical sectors, to help physically disabled people in their quotidian lives. Therefore, the research of robotics applied in the control of an anthropomorphic robotic arm to people assistance and rehabilitation has increased considerably. In this context, robotic control is one of the most important problems and is considered the main part of trajectory planning and motion control. The main solution for robotic control is inverse-kinematics, because it provides the angles of robotic arm joints. However, there are disadvantages in the algorithms presented by several authors because the trajectory calculation needs an optimization process which implies more calculations to generate an optimized trajectory. Moreover, the solutions presented by the authors implied devices where the people are dependent or require help from other people to control these devices. This article proposes an algorithm to calculate an accuracy trajectory in any time of interest using an LCD touch screen to calculate the inverse-kinematics and get the end-point of the gripper; the trajectory is calculated using a novel distribution function proposed which makes an easy way to get fast results to the trajectory planning. The obtained results show improvements to generate a safe and fast trajectory of an anthropomorphic robotic arm using an LCD touch screen allowed calculating short trajectories with minimal fingers moves.

[Robotic assistance in activities of daily living exemplified by food intake]

Carrying out activities of daily living (ADL, also called basic activities) is limited or even no longer possible due to functional limitations and functional losses associated with aging, (chronic) illness and disabilities. Nowadays, there are a variety of assistive technologies/devices and even robotic products. The aim of this article is to give an exemplary overview of the existing products for the basic activity of food intake for people with tetraplegia caused by accidents or neurological disorders, such as multiple sclerosis or amyotrophic lateral sclerosis (ALS). The dissemination and implementation of these products seems to be relatively low in Germany. Inhibiting and promoting factors for the dissemination and utilization are discussed.

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

Individuals suffering from quadriplegia can achieve increased independence by using an assistive robotic manipulator (ARM). However, due to their disability, the interfaces that can be used to operate such devices become limited. A versatile intraoral tongue control interface (ITCI) has previously been develop for this user group, as the tongue is usually spared from disability. A previous study has shown that the ITCI can provide direct and continuous control of 6-7 degrees of freedom (DoF) of an ARM, due to a high number of provided inputs (18). In the present pilot study we investigated whether semi-automation might further improve the efficiency of the ITCI, when controlling an ARM. This was achieved by adding a camera to the end effector of the ARM and using computer vision algorithms to guide the ARM to grasp a target object. Three ITCI and one joystick control scheme were tested and compared: 1) manual Cartesian control with a base frame reference point, 2) manual Cartesian control with an end effector reference point 3) manual Cartesian control with an end effector reference point and an autonomous grasp function 4) regular JACO² joystick control. The results indicated that end effector control was superior to the base frame control in total task time, number of commands issued and path efficiency. The addition of the automatic grasp function did not improve the performance, but resulted in fewer collisions/displacements of the target object when grasping.

Manual Feeding Device Experiences of People With a Neurodisability

OBJECTIVE. Neurological bilateral upper limb weakness can result in self-feeding difficulties and reliance on care providers. Mealtimes become time consuming and frustrating. In this exploratory inquiry, we examined the experiences of users of a feeding device.

METHOD. Semistructured interviews were either conducted by telephone or administered via email to explore quality of life, changes to independence, benefits and limitations, and psychological impact of the equipment.

RESULTS. Thematic analysis gave rise to five themes: independence and positivity, emotions, impact on family and social life, equipment functionality, and motivation.

CONCLUSION. This exploratory inquiry has contributed new qualitative evidence to the knowledge and understanding of users’ experiences of a manual feeding device. Users reported that the need for assistance was reduced and that their quality of life, independence, and freedom improved. Time and resources savings for the family, care providers, and staff appeared to result in a more equal relationship between user and care provider.

Wireless intraoral tongue control of an assistive robotic arm for individuals with tetraplegia

BACKGROUND

For an individual with tetraplegia assistive robotic arms provide a potentially invaluable opportunity for rehabilitation. However, there is a lack of available control methods to allow these individuals to fully control the assistive arms.

METHODS

Here we show that it is possible for an individual with tetraplegia to use the tongue to fully control all 14 movements of an assistive robotic arm in a three dimensional space using a wireless intraoral control system, thus allowing for numerous activities of daily living. We developed a tongue-based robotic control method incorporating a multi-sensor inductive tongue interface. One abled-bodied individual and one individual with tetraplegia performed a proof of concept study by controlling the robot with their tongue using direct actuator control and endpoint control, respectively.

RESULTS

After 30 min of training, the able-bodied experimental participant tongue controlled the assistive robot to pick up a roll of tape in 80% of the attempts. Further, the individual with tetraplegia succeeded in fully tongue controlling the assistive robot to reach for and touch a roll of tape in 100% of the attempts and to pick up the roll in 50% of the attempts. Furthermore, she controlled the robot to grasp a bottle of water and pour its contents into a cup; her first functional action in 19 years.

CONCLUSION

To our knowledge, this is the first time that an individual with tetraplegia has been able to fully control an assistive robotic arm using a wireless intraoral tongue interface. The tongue interface used to control the robot is currently available for control of computers and of powered wheelchairs, and the robot employed in this study is also commercially available. Therefore, the presented results may translate into available solutions within reasonable time.