Documenti accessibili
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Informazioni generali |
| Autore |
Bethencourt, Aymeric; Jaulin, Luc |
| Pubblicato |
InTech Open Access Publisher, 2013
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| edizione |
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| ISBN |
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| Abstract |
The principle behind VSLAM applications like
3D object reconstruction or indoor mapping is to estimate
the spatial transformation between two large clouds of
points, which represent two poses of the same scene.
They can further be processed to obtain detailed surfaces.
Since its introduction in 1992, the standard algorithm for
finding the alignment between two point clouds is ICP
(Iterative Closest Point) and its variants, combined with
RANSAC (RANdom SAmple Consensus). This paper
presents a new approach using interval analysis. The idea
is to define large intervals for the transformation
parameters between the poses then to successively
contract those intervals using the equations of the
transformation of corresponding points between the
poses. To contract those intervals faster, we added an
IMU (Inertial Measurement Unit) to our system so the
initial intervals of the parameters are already small before
applying the contractions. We implemented our
algorithm using the middleware ROS (Robot Operating
System) and stated our performances. |
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International Journal of Advanced Robotic Systems
Autore: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Pubblicato: 2004
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