Intuitive adaptive orientation control of assistive robots for people living with upper limb disabilities

Abstract

Robotic assistive devices enhance the autonomy of individuals living with physical disabilities in their day-to-day life. Although the first priority for such devices is safety, they must also be intuitive and efficient from an engineering point of view in order to be adopted by a broad range of users. This is especially true for assistive robotic arms, as they are used for the complex control tasks of daily living. One challenge in the control of such assistive robots is the management of the end-effector orientation which is not always intuitive for the human operator, especially for neophytes. This paper presents a novel orientation control algorithm designed for robotic arms in the context of human-robot interaction. This work aims at making the control of the robot's orientation easier and more intuitive for the user, in particular, individuals living with upper limb disabilities. The performance and intuitiveness of the proposed orientation control algorithm is assessed through two experiments with 25 able-bodied subjects and shown to significantly improve on both aspects.

Transfer learning for sEMG hand gestures recognition using convolutional neural networks

“…The wrist extension, flexion, ulnar deviation and radial deviation gestures rotate the robotic hand in the same direction as the gesture performed. This behavior is achieved using the rotation system proposed in [42] which was shown to be easier to use than classic robot end-effector rotation. Finally, the closed and opened hand gesture were used to close and open the robotic hand respectively.…”

Assistive robotic arm: Evaluation of the performance of intelligent algorithms

“…This could be due to multiple factors such as few available independent control signals, lack of fine movements to perform precision tasks such as picking up a straw and severe user's spasms. To overcome these difficulties, different solutions were proposed in the literature, such as alternative control interfaces (accelerometers (Fall et al, 2015), EMG (Côté-Allard et al, 2017), computer-vision (Ka et al, 2016) and control algorithms (Vu et al, 2017;Herlant et al, 2016;Campeau-Lecours et al, 2016).…”

Helping People Through Space and Time: Assistance as a Perspective on Human-Robot Interaction

“…Shared control, especially when an input controller (e.g., a joystick) limits the number of input degrees of freedom (Aronson et al, 2018), can also be made easier for user's by providing assistance that alters the user's mental state. A robot arm can assist its user by maintaining more easily controllable state configurations (Javdani et al, 2015;Till et al, 2015;Vu et al, 2017;Aronson et al, 2018;Newman et al, 2018) or by optimizing which degrees of freedom the user can control at any given time (Herlant et al, 2016). This idea can be extended to supernumerary arms that provide users with an additional appendage but are difficult to control (Nakabayashi et al, 2018;Vatsal and Hoffman, 2018), teleoperating robotic arms through electromyography (Noda et al, 2013;Pham et al, 2017) or similar sensing devices (Muratore et al, 2019), or humanoid robots (Lin et al, 2019;Zhou et al, 2019).…”