robotic wheelchair
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Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 168
Author(s):  
Mohsen Bakouri ◽  
Mohammed Alsehaimi ◽  
Husham Farouk Ismail ◽  
Khaled Alshareef ◽  
Ali Ganoun ◽  
...  

Many wheelchair people depend on others to control the movement of their wheelchairs, which significantly influences their independence and quality of life. Smart wheelchairs offer a degree of self-dependence and freedom to drive their own vehicles. In this work, we designed and implemented a low-cost software and hardware method to steer a robotic wheelchair. Moreover, from our method, we developed our own Android mobile app based on Flutter software. A convolutional neural network (CNN)-based network-in-network (NIN) structure approach integrated with a voice recognition model was also developed and configured to build the mobile app. The technique was also implemented and configured using an offline Wi-Fi network hotspot between software and hardware components. Five voice commands (yes, no, left, right, and stop) guided and controlled the wheelchair through the Raspberry Pi and DC motor drives. The overall system was evaluated based on a trained and validated English speech corpus by Arabic native speakers for isolated words to assess the performance of the Android OS application. The maneuverability performance of indoor and outdoor navigation was also evaluated in terms of accuracy. The results indicated a degree of accuracy of approximately 87.2% of the accurate prediction of some of the five voice commands. Additionally, in the real-time performance test, the root-mean-square deviation (RMSD) values between the planned and actual nodes for indoor/outdoor maneuvering were 1.721 × 10−5 and 1.743 × 10−5, respectively.


Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7810
Author(s):  
Sivashankar Sivakanthan ◽  
Jeremy Castagno ◽  
Jorge L. Candiotti ◽  
Jie Zhou ◽  
Satish Andrea Sundaram ◽  
...  

Common electric powered wheelchairs cannot safely negotiate architectural barriers (i.e., curbs) which could injure the user and damage the wheelchair. Robotic wheelchairs have been developed to address this issue; however, proper alignment performed by the user is needed prior to negotiating curbs. Users with physical and/or sensory impairments may find it challenging to negotiate such barriers. Hence, a Curb Recognition and Negotiation (CRN) system was developed to increase user’s speed and safety when negotiating a curb. This article describes the CRN system which combines an existing curb negotiation application of a mobility enhancement robot (MEBot) and a plane extraction algorithm called Polylidar3D to recognize curb characteristics and automatically approach and negotiate curbs. The accuracy and reliability of the CRN system were evaluated to detect an engineered curb with known height and 15 starting positions in controlled conditions. The CRN system successfully recognized curbs at 14 out of 15 starting positions and correctly determined the height and distance for the MEBot to travel towards the curb. While the MEBot curb alignment was 1.5 ± 4.4°, the curb ascending was executed safely. The findings provide support for the implementation of a robotic wheelchair to increase speed and reduce human error when negotiating curbs and improve accessibility.


Author(s):  
Muhammad Aminur Rahaman ◽  
Md Jahidul Islam ◽  
Sumaiya Kabir ◽  
Ayesha Khatun

Currently, thousands of people are suffering from paralysis. They have difficulties with speaking and walking. So we’ve developed a new kind of robot that can help those people who can’t walk or speak. By utilizing this robot (hand gloves or wheelchair handle) and gesture-based regulators, people with physical disabilities will improve their quality of life. The robot of the proposal has two components, one is the controller of the motion, and the other is the Robotic Wheelchair (RW). Where one can easily interact with the robotic-base wheelchair-using sensor-based hand gesture. With this human-robot interaction, a patient can quite easily control the robot and can move freely. In addition, the required patients may use gestures (hand gloves or wheelchair handle) to express their needs. Furthermore, we will reduce the effort to regulate the RW and hand movements with this device, that’s really difficult for disabled or dumb people. Our device can run with approximately 94% accuracy and very minimal delay. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 7, Dec 2020 P 85-93


Author(s):  
Jorge Candiotti ◽  
Brandon Daveler ◽  
Sivashankar Sivakanthan ◽  
Garrett Grindle ◽  
Rosemarie Cooper ◽  
...  
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2020 ◽  
Vol 10 (1) ◽  
pp. 1-23
Author(s):  
Mohammed Kutbi ◽  
Xiaoxue Du ◽  
Yizhe Chang ◽  
Bo Sun ◽  
Nikolaos Agadakos ◽  
...  

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