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|Type:||Artigo de evento|
|Title:||Real-time Collision Risk Estimation Based On Pearson's Correlation Coefficient|
|Author:||Miranda Neto A.|
|Abstract:||The perception of the environment is a major issue in autonomous robots. In our previous works, we have proposed a visual perception system based on an automatic image discarding method as a simple solution to improve the performance of a real-time navigation system. In this paper, we take place in the obstacle avoidance context for vehicles in dynamic and unknown environments, and we propose a new method for Collision Risk Estimation based on Pearson's Correlation Coefficient (PCC). Applying the PCC to real-time CRE has not been done yet, making the concept unique. This paper provides a novel way of calculating collision risk and applying it for object avoidance using the PCC. This real-time perception system has been evaluated from real data obtained by our intelligent vehicle. © 2013 IEEE.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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