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arXiv · 1210.1104

Sensory Anticipation of Optical Flow in Mobile Robotics

Arturo Ribes·Jesús Cerquides·Yiannis Demiris·Ramón López de Mántaras
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Abstract

In order to anticipate dangerous events, like a collision, an agent needs to make long-term predictions. However, those are challenging due to uncertainties in internal and external variables and environment dynamics. A sensorimotor model is acquired online by the mobile robot using a state-of-the-art method that learns the optical flow distribution in images, both in space and time. The learnt model is used to anticipate the optical flow up to a given time horizon and to predict an imminent collision by using reinforcement learning. We demonstrate that multi-modal predictions reduce to simpler distributions once actions are taken into account.

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Arturo Ribes, Jesús Cerquides, Yiannis Demiris, Ramón López de Mántaras. 2012-10-03. Sensory Anticipation of Optical Flow in Mobile Robotics. https://arxiv.org/abs/1210.1104

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