Hybrid position and orientation tracking for a passive rehabilitation table-top robot
| Autor: | Andrew Jackson, Martin Levesley, Justin Gallagher, Peter Culmer, K. K. Wojewoda |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
Robot calibration ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 02 engineering and technology law.invention 03 medical and health sciences 0302 clinical medicine law 0202 electrical engineering electronic engineering information engineering Humans Computer vision Simulation Aged 80 and over Robot kinematics Internet business.industry Stroke Rehabilitation Tracking system Robotics Equipment Design Robot end effector Robot control Exercise Therapy Robot 020201 artificial intelligence & image processing Female Artificial intelligence business Robotic arm 030217 neurology & neurosurgery Algorithms |
| Zdroj: | ICORR |
| ISSN: | 1945-7901 |
| Popis: | This paper presents a real time hybrid 2D position and orientation tracking system developed for an upper limb rehabilitation robot. Designed to work on a table-top, the robot is to enable home-based upper-limb rehabilitative exercise for stroke patients. Estimates of the robot's position are computed by fusing data from two tracking systems, each utilizing a different sensor type: laser optical sensors and a webcam. Two laser optical sensors are mounted on the underside of the robot and track the relative motion of the robot with respect to the surface on which it is placed. The webcam is positioned directly above the workspace, mounted on a fixed stand, and tracks the robot's position with respect to a fixed coordinate system. The optical sensors sample the position data at a higher frequency than the webcam, and a position and orientation fusion scheme is proposed to fuse the data from the two tracking systems. The proposed fusion scheme is validated through an experimental set-up whereby the rehabilitation robot is moved by a humanoid robotic arm replicating previously recorded movements of a stroke patient. The results prove that the presented hybrid position tracking system can track the position and orientation with greater accuracy than the webcam or optical sensors alone. The results also confirm that the developed system is capable of tracking recovery trends during rehabilitation therapy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|