Comparative study on obstacle detection and avoidance system by using real-time Image Processing and Artificial Intelligence in autonomous wheelchair application

Yoon Ket Lee, Shang Deen Tan, Yeh Huann Goh, Chern Hong Lim

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch


The research objective of this project conducts a comparative performance study between real time image processing and Artificial Intelligence object recognition in the application of obstacle avoidance system for an autonomous wheelchair. The proposed obstacle detection system is achieved through the application of camera sensor with the implementation of Artificial Intelligence techniques in image processing. A pre-trained Convolutional Neural Network model known as MobileNet SSD, and Deep Neural Network (DNN) module in OpenCV library (for live video streams) are utilized in developing the object recognition algorithm. An Arduino and a pair of DC brushed motors together with Smart Drive 40 motor drivers made up the motion control system that acts correspondingly to the inputs obtained from the obstacle detection system(s). Comparative researches on the performance of both obstacle detection algorithms were carried out experimentally. The considered performance is the success rate in obstacle avoidance and this performance was analyzed based on varying light intensity, motor speed, and wall detection. The results obtained indicate that Artificial Intelligence based obstacle detection algorithm performed better than real time image processing with vary light intensity environment. However, it has a relatively low performance with varying motor speed and wall detection when compared to the Image Processing based obstacle detection system.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2019
EditorsBing Xu
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781728105130, 9781728105123
ISBN (Print)9781728105147
Publication statusPublished - 2019
Externally publishedYes
EventIEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference 2019 - Chongqing, China
Duration: 11 Oct 201913 Oct 2019
Conference number: 3rd (Proceedings)


ConferenceIEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference 2019
Abbreviated titleIMCEC 2019
Internet address


  • Image Processing
  • Object Recognition
  • Obstacle Avoidance

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