Human-Machine Interface for a Smart Wheelchair
The paper describes the integration of hardware and software with sensor technology and computer processing to develop the next generation intelligent wheelchair. The focus is a computer cluster design to test high performance computing for smart wheelchair operation and human interaction. The LabVI...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2019/4837058 |
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| _version_ | 1832567629292765184 |
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| author | Amiel Hartman Vidya K. Nandikolla |
| author_facet | Amiel Hartman Vidya K. Nandikolla |
| author_sort | Amiel Hartman |
| collection | DOAJ |
| description | The paper describes the integration of hardware and software with sensor technology and computer processing to develop the next generation intelligent wheelchair. The focus is a computer cluster design to test high performance computing for smart wheelchair operation and human interaction. The LabVIEW cluster is developed for real-time autonomous path planning and sensor data processing. Four small form factor computers are connected over a Gigabit Ethernet local area network to form the computer cluster. Autonomous programs are distributed across the cluster for increased task parallelism to improve processing time performance. The distributed programs operating frequency for path planning and motion control is 50Hz and 12.3Hz for 0.3 megapixel robot vision system. To monitor the operation and control of the distributed LabVIEW code, network automation is integrated into the cluster software along with a performance monitor. A link between the computer motion control program and the wheelchair joystick control of the drive train is developed for the computer control interface. A perception sensor array and control circuitry is integrated with the computer system to detect and respond to the wheelchair environment. Multiple cameras are used for image processing and scanning laser rangefinder sensors for obstacle avoidance in the cluster program. A centralized power system is integrated to power the smart wheelchair along with the cluster and sensor feedback system. The on board computer system is evaluated for cluster processing performance for the smart wheelchair, incorporating camera machine vision and LiDAR perception for terrain obstacle detection, operating in urban scenarios. |
| format | Article |
| id | doaj-art-fc23165f05c24f4eb3c508ec09954a94 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-fc23165f05c24f4eb3c508ec09954a942025-02-03T01:01:11ZengWileyJournal of Robotics1687-96001687-96192019-01-01201910.1155/2019/48370584837058Human-Machine Interface for a Smart WheelchairAmiel Hartman0Vidya K. Nandikolla1College of Engineering and Computer Science, California State University at Northridge, CA, USACollege of Engineering and Computer Science, California State University at Northridge, CA, USAThe paper describes the integration of hardware and software with sensor technology and computer processing to develop the next generation intelligent wheelchair. The focus is a computer cluster design to test high performance computing for smart wheelchair operation and human interaction. The LabVIEW cluster is developed for real-time autonomous path planning and sensor data processing. Four small form factor computers are connected over a Gigabit Ethernet local area network to form the computer cluster. Autonomous programs are distributed across the cluster for increased task parallelism to improve processing time performance. The distributed programs operating frequency for path planning and motion control is 50Hz and 12.3Hz for 0.3 megapixel robot vision system. To monitor the operation and control of the distributed LabVIEW code, network automation is integrated into the cluster software along with a performance monitor. A link between the computer motion control program and the wheelchair joystick control of the drive train is developed for the computer control interface. A perception sensor array and control circuitry is integrated with the computer system to detect and respond to the wheelchair environment. Multiple cameras are used for image processing and scanning laser rangefinder sensors for obstacle avoidance in the cluster program. A centralized power system is integrated to power the smart wheelchair along with the cluster and sensor feedback system. The on board computer system is evaluated for cluster processing performance for the smart wheelchair, incorporating camera machine vision and LiDAR perception for terrain obstacle detection, operating in urban scenarios.http://dx.doi.org/10.1155/2019/4837058 |
| spellingShingle | Amiel Hartman Vidya K. Nandikolla Human-Machine Interface for a Smart Wheelchair Journal of Robotics |
| title | Human-Machine Interface for a Smart Wheelchair |
| title_full | Human-Machine Interface for a Smart Wheelchair |
| title_fullStr | Human-Machine Interface for a Smart Wheelchair |
| title_full_unstemmed | Human-Machine Interface for a Smart Wheelchair |
| title_short | Human-Machine Interface for a Smart Wheelchair |
| title_sort | human machine interface for a smart wheelchair |
| url | http://dx.doi.org/10.1155/2019/4837058 |
| work_keys_str_mv | AT amielhartman humanmachineinterfaceforasmartwheelchair AT vidyaknandikolla humanmachineinterfaceforasmartwheelchair |