Development of computer vision based obstacle detection and human tracking on smart wheelchair for disabled patient

People with physical disability such as quadriplegics may need a device which assist their mobility. Smart wheelchair is developed based on conventional wheelchair and is also generally equipped with sensors, cameras and computer based system as main processing unit to be able to perform specific algorithm for the intelligent capabilities. We develop smart wheelchair system that facilitates obstacle detection and human tracking based on computer vision. The experiment result of obstacle distance estimation using RANSAC showed lower average error, which is only 1.076 cm compared to linear regression which is 2.508 cm. The average accuracy of human guide detecting algorithm also showed acceptable result, which yield over 80% of accuracy.

[1]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[2]  Saiyan Saiyod,et al.  Obstacle detection algorithm for unmanned aerial vehicles using binocular stereoscopic vision , 2017, 2017 9th International Conference on Knowledge and Smart Technology (KST).

[3]  Fitri Utaminingrum,et al.  Fast Obstacle Distance Estimation using Laser Line Imaging Technique for Smart Wheelchair , 2016 .

[4]  Fitri Utaminingrum,et al.  Eye Movement as Navigator for Disabled Person , 2016, ICCIS '16.

[5]  P. Meena,et al.  A novel strategy for controlling the movement of a smart wheelchair using internet of things , 2014, 2014 IEEE Global Humanitarian Technology Conference - South Asia Satellite (GHTC-SAS).

[6]  Christoph Ruland,et al.  Content based image authentication using HOG feature descriptor , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[7]  Rubén Posada-Gómez,et al.  Obstacle avoidance embedded system for a smart wheelchair with a multimodal navigation interface , 2014, 2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE).

[8]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[9]  Ilham Priadythama,et al.  Review of intelligent wheelchair technology control development in the last 12 years , 2016, 2016 2nd International Conference of Industrial, Mechanical, Electrical, and Chemical Engineering (ICIMECE).

[10]  Mohammad Mahdi Dehshibi,et al.  HOG and LBP: Towards a robust face recognition system , 2015, 2015 Tenth International Conference on Digital Information Management (ICDIM).

[11]  Fitri Utaminingrum,et al.  A laser-vision based obstacle detection and distance estimation for smart wheelchair navigation , 2016, 2016 IEEE International Conference on Signal and Image Processing (ICSIP).

[12]  R. Simpson,et al.  How many people would benefit from a smart wheelchair? , 2008, Journal of rehabilitation research and development.

[13]  Takakazu Ishimatsu,et al.  Improvement of a Joystick Controller for Electric Wheelchair User , 2015 .

[14]  Chiharu Ishii,et al.  Control of an electric wheelchair with a brain-computer interface headset , 2016, 2016 International Conference on Advanced Mechatronic Systems (ICAMechS).

[15]  Jingchuan Wang,et al.  A control system of driver assistance and human following for smart wheelchair , 2014, 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014).

[16]  Shraddha Uddhav Khadilkar,et al.  Android phone controlled voice, gesture and touch screen operated smart wheelchair , 2015, 2015 International Conference on Pervasive Computing (ICPC).

[17]  Fitri Utaminingrum,et al.  Road detection based on the color space and cluster connecting , 2016, 2016 IEEE International Conference on Signal and Image Processing (ICSIP).

[18]  Konstantinos G. Derpanis,et al.  Overview of the RANSAC Algorithm , 2005 .

[19]  R. A. Hamzah,et al.  An obstacle detection and avoidance of a mobile robot with stereo vision camera , 2011, 2011 International Conference on Electronic Devices, Systems and Applications (ICEDSA).