ICRA 2011 Paper Abstract


Paper TuP114.5

Di Corato, Francesco (University of Pisa), Innocenti, Mario (University of Pisa), Indiveri, Giovanni (University of Salento), Pollini, Lorenzo (University of Pisa)

An Entropy–Like Approach to Vision Based Autonomous Navigation

Scheduled for presentation during the Regular Sessions "Visual Navigation III" (TuP114), Tuesday, May 10, 2011, 14:40−14:55, Room 5J

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on April 2, 2020

Keywords Visual Navigation, Autonomous Navigation, Computer Vision for Robotics and Automation


This article proposes a novel solution to the Pose Estimation problem for Ego–Motion from stereo camera images. The approach uses an Entropy–Like cost function which is robust by nature to the presence of noise and outliers in the visual features. The SIFT algorithm is used to collect and match the features from stereo images. The 3– vectors quaternion parameterization is used to parameterize the rotation matrix, in order to avoid the unit norm constraint in the minimization computation. Simulations and experimental results are presented and compared with the results obtained via the classical Iterative Closest Point approach.



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