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충돌 및 균형상실 사고 방지를 위한 스마트폰 연동 전동 휠체어

Electric Wheelchair Connected to Smartphone for Preventing Accident from Collision and Lost of Balance

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초록

This research has been conducted to develop a prevention module of collision and balance lost in electric wheelchairs. Ultrasonic sensors were used for detecting obstacles. Giro and acceleration sensors were used for measuring the tilt angle of wheel chair frame. Kalman filters were employed for filtering high-frequency noise of acceleration sensor and removing zero drift of the Giro sensor. The presence and location of obstacles were detected, and their information was sent to the user smartphone. When the tilt angle of the wheelchair frame exceeded a certain value, a warning signal was set to operate. Raspberry Pi camera module was used to transfer rear view image data to the smartphone to help the driver acknowledge obstacles in the rear side. A DSP processor with high computing performance was necessary to realize a real-time processing of the sensor and image data. Our research showed that a prevention module of collision and balance lost connected to a smartphone can be realized at a considerable low price.

Abstract

This research has been conducted to develop a prevention module of collision and balance lost in electric wheelchairs. Ultrasonic sensors were used for detecting obstacles. Giro and acceleration sensors were used for measuring the tilt angle of wheel chair frame. Kalman filters were employed for filtering high-frequency noise of acceleration sensor and removing zero drift of the Giro sensor. The presence and location of obstacles were detected, and their information was sent to the user smartphone. When the tilt angle of the wheelchair frame exceeded a certain value, a warning signal was set to operate. Raspberry Pi camera module was used to transfer rear view image data to the smartphone to help the driver acknowledge obstacles in the rear side. A DSP processor with high computing performance was necessary to realize a real-time processing of the sensor and image data. Our research showed that a prevention module of collision and balance lost connected to a smartphone can be realized at a considerable low price.

참고문헌 (11)

  1. Electric Motion Assisting Device(Powered Wheelchair Electric Scooter)Using State Survey, "The Korean Consumer Agency", The Korean Consumer Agency, 29~31 (2015)
  2. Y. R. Lee, "A Rear Alarm System using Ultra-sonic Wave Sensor", The Speleological Society, 79, pp.47~51 (2007)
  3. D. J. Jang, "Study on Dynamic Stability Analysis of Electric Wheelchair", Fall Conference of Korean Society for Precision Engineering, pp.612~613 (2016)
  4. 최윤규, "지향각이 넓은 저가의 초음파센서를 이용한 이동로봇의 장애물 회피", 제어.로봇.시스템학회 논문지, 15(11), pp.1102~1107 (2009), 제어·로봇·시스템학회
  5. 여희주, "원격제어 이동로봇의 장애물 회피를 위한 퍼지 제어", 전자공학회논문지 - SC, 48(1), pp.47~54 (2011), 대한전자공학회
  6. David A. Sanders, "Using Self-Reliance Factors to Decide How to Share Control Between Human Powered Wheelchair Drivers and Ultrasonic Sensors", IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(8), pp.1221~1229 (2017)
  7. D. K. Heo, "Development of Management App. of Powered Wheelchair", Summer Conference of Rehabilitation Engineering And Assistive Technology Society of Korea, pp.96~98 (2017)
  8. M. G. Hwang, "Smart Phone Based Electronic Wheel Chair Location and Situation Monitoring System", Proceedings of the Korean Society of Compurter Information Conference, 22(2), pp.411~414 (2014)
  9. Y. G. Jei, "Self Driving System of Wheelchair using Smartphone", Korean Patent Number 10-2019-0049469, ~ (2019)
  10. S. P. Kim, "Understanding of Kalman Filter Using MATLAB" (2010), A-Jin Publishing Company
  11. Johann B., "Error Eliminating Rapid Ultrasonic Firing for Mobile Robot Obstacle Avoidance", IEEE Transactions on Robotics and Automation, 11(1), pp.132~138 (1995)

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