LEARNING OBSTACLE BEHAVIOR FOR IMPROVED THREAT MAPPING DURING NAVIGATION
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Date
2016-05-03
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Johns Hopkins University
Abstract
A novel obstacle evaluation system for the visually impaired is proposed and evaluated in
this thesis. This system assesses the threat in the environment posed by various kinds of
stationary and moving obstacles. It evaluates the behaviors of different classes of
obstacles and learns features based on their collision avoidance strategies. For the
purpose of crowd simulation, Reciprocal Collision Avoidance strategy has been used
here. This idea can further be generalized to any multi-agent environment and can serve
as the building block for new obstacle avoidance algorithms.
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Keywords
visually impaired, obstacle avoidance, collision avoidance, multi agent, threat map