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Optimizing Wearable Assistive Devices With Neuromuscular Models And Optimal Control, Manish Sreenivasa, Matthew Millard, Paul Manns, Katja Mombaur
Optimizing Wearable Assistive Devices With Neuromuscular Models And Optimal Control, Manish Sreenivasa, Matthew Millard, Paul Manns, Katja Mombaur
Faculty of Engineering and Information Sciences - Papers: Part B
The coupling of human movement dynamics with the function and design of wearable assistive devices is vital to better understand the interaction between the two. Advanced neuromuscular models and optimal control formulations provide the possibility to study and improve this interaction. In addition, optimal control can also be used to generate predictive simulations that generate novel movements for the human model under varying optimization criterion.
Pedestrian Lane Detection For Assistive Navigation Of Blind People, M Le, Son Lam Phung, Abdesselam Bouzerdoum
Pedestrian Lane Detection For Assistive Navigation Of Blind People, M Le, Son Lam Phung, Abdesselam Bouzerdoum
Faculty of Engineering and Information Sciences - Papers: Part A
Navigating safely in outdoor environments is a challenging activity for vision-impaired people. This paper is a step towards developing an assistive navigation system for the blind. We propose a robust method for detecting the pedestrian marked lanes at traffic junctions. The proposed method includes two stages: regions of interest (ROI) extraction and lane marker verification. The ROI extraction is performed by using colour and intensity information. A probabilistic framework employing multiple geometric cues is then used to verify the extracted ROI. The experimental results have shown that the proposed method is robust under challenging illumination conditions and obtains superior performance …