Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six degrees of freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments. © 2013 Springer Science+Business Media New York.
CITATION STYLE
Viejo, D., & Cazorla, M. (2014). A robust and fast method for 6DoF motion estimation from generalized 3D data. Autonomous Robots, 36(4), 295–308. https://doi.org/10.1007/s10514-013-9354-z
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