Blind Travel Prediction Based on Obstacle Avoidance in Indoor Scene

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Abstract
Blind people have intelligent tools to rely on for travel with the development of navigation technology. The GPS navigation, blind track, etc., are tools that blind people often use when traveling outdoors. However, indoor navigation tools and technology for blind people are lacking. We propose an obstacle avoidance algorithm and a spatial‐temporal model of trajectory prediction for the indoor travel task of the blind. The focus of this work is that it enables the blind to accurately avoid obstacles and achieve high accuracy trajectory prediction aiming at the unique movement characteristics of the blind. We set up a variety of baselines to conduct an experimental evaluation on a dataset of blind trajectories in a multistorey shopping mall. The experimental results show the advantages of the data model and predictive model of this work.
Funding Information
  • China Postdoctoral Science Foundation (2018M642613)
  • National Natural Science Foundation of China (61802216)
  • Natural Science Foundation of Shandong Province (ZR2020MF060)

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