Hazard-free outdoor path navigator for visually challenged people.

Abstract

A multi-technology approach is helpful for challenging people to sense, localisation and user-centred route maps to navigate between destinations. Visually challenged people need navigation assistance between source and destination to choose a hazard-free or minimal-hazard optimal path. Navigator invokes online and offline hazard-free route maps to establish a safe and optimised route between source and destination. An online navigation system finds hazard-free optimal paths by artificial intelligence (AI), deep learning (DL), machine learning (ML) and cloud. The offline navigator uses a tensor processing unit (TPU) to generate a path map. Navigator uses AI and DL techniques to identify tree branches, signboards, underside of parked vehicles, open glass windows bumping into another walking person and fast-moving objects in outdoors and predicts artificial and natural hazards for selecting hazard-free optimised paths. The proposed fuzzy trusted hazard free routing path (FTHRP) algorithm utilises the data set "hazard-route data set" to identify the obstacle-free path between the source and destination by path planning and dynamic re-routing to avoid unexpected hazards. The navigation system leverages semantic route mapping based on AI-driven context inference processed by hardware and software.