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Target recognition is a fundamental research topic in the process of robot grasping. In this paper, we proposed an algorithm framework for object recognition based on local naive Bayes nearest neighbor with Kinect. With the emergence of local invariant feature detection, the method based on local invariant features gradually becomes the mainstream. Object recognition is realized through the feature...
In this paper we present a novel method called color support Normal Iterative Closest Point (color NICP) to recursively align point clouds. First of all, the matching criterion of NICP is improved based on the uncertainty analysis on the feature points and L∗a∗b∗ color space. Secondly, a six-dimensional k-d tree based nearest neighbor search is used to match corresponding points between the clouds...
In dense 3D SLAM (simultaneous localization and mapping), the use of RGB-D data to realize SLAM has become more widespread. In this paper, PRKF (the precise and robust KinectFusion) is proposed. On the basis of KinectFusion, the graph optimization based on g2o (general graph optimization) is added to the PRKF. In the g2o optimization policy, in order to achieve the rapid optimization of error accumulation,...
Restricted by environmental noise and the sensor itself performances, environmental information collected by various sensors of mobile robot has certain uncertainty. Laser Range Finder (LRF) has high precise measurement and large measuring range, but it can only acquire the environment information at a certain level, especially, it is unable to detect obstacles below the level of LRF measuring, so...
In this paper, a monocular 3D dense reconstruction technique based on optical flow feedback is proposed to achieve fast and accurate 3D stereoscopic modeling in the real scene. Corresponding pixel pairs are robustly matched by inter-frame optical flow fields, and the five-point algorithm is employed to determine relative pose of the moving camera, based on which sparse point cloud is generated and...
The main objective of this paper is to develop 3D point cloud alignment technique by using an improved absolute orientation algorithm based on unit quaternion. In this method, Scale Invariant Features Transform (SIFT) is used to find corresponding feature points, and Random Sample Consensus (RANSAC) is used as robust estimator to remove false matches in the point cloud group. The unit quaternion solution...
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