Disabled patients with partial and total loss of functions in their limbs require continuous dedicated assistance both in the hospital and in their home. This need can be alleviated by the use of robotic assistive devices, which patients can employ to perform basic movements, for example to reach to food or drink items, thus acquiring a certain degree of independence. In Kazakhstan, the availability of medical and rehabilitation services is minimal, and there are currently no assistive devices available to patients with this type of disabilities. This poses the challenge of designing suitable human-machine interfaces (HMI) providing these patients with the ability to control external assistive devices.
Aims and objectives
This project aims to develop a novel assistive robotic system for disabled people based on the use of a joystick controlled and non-invasive human-brain interfaces for the control of a sensor rich robotic arm. This development has large potential for clinical applications, as it will offer disabled and paralised patients in Kazakhstan a non-invasive approach to perform purposeful manipulations and improve their quality of life.
– An PC based controlled interface for real-time motion control of a collaborative Universal Robots UR5 and Kinova Jaco assistive robotic arm were developed;
– A brain-machine interface (BMI) developed by Dr. Berdakh Abibullaev is connected to the Universal Robots UR5 arm for direct brain-robot control design
Previously, the developed BMI was tested on a Jaguar mobile robot
M. Rubagotti, T. Taunyazov, B. Omarali, A. Shintemirov, Semi-Autonomous Robot Teleoperation with Obstacle Avoidance Via Model Predictive Control , IEEE Robotics and Automation Letters, vol. 4(3): 2746 – 2753, 2019 IEEE Xplore pdf
S. Rakhimkul, A. Kim, A. Pazylbekov, A. Shintemirov, Autonomous Object Detection and Grasping Using Deep Learning for Design of an Intelligent Assistive Robot Manipulation System, IEEE International Conference on Systems, Man and Cybernetics (IEEE SMC 2019), Italy, 2019, accepted
B. Omarali, T. Taunyazov, A. Bukeyev, A. Shintemirov, Real-Time Predictive Control of an UR5 Robotic Arm Through Human Upper Limb Motion Tracking, The 2017 ACM/IEEE International Conference on Human-Robot Interaction (HRI2017), Austria, 2017 ACM DL pdf
D. Nurseitov, A. Serekov, A. Shintemirov, B. Abibullaev, Design and Evaluation of a P300-ERP based BCI System for Real-Time Control of a Mobile Robot, The 5th International Winter Conference on Brain-Computer Interface, South Korea, 2017 IEEE Xplore