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Robots are still not able to grasp all unforeseen objects. Finding a proper grasp configuration, i.e. the position and orientation of the arm relative to the object, is still challenging. One approach for grasping unforeseen objects is to recognize an appropriate grasp configuration from previous grasp demonstrations. The underlying assumption in this approach is that new objects that are similar...
Enabling a robot to grasp unknown objects is still an ongoing challenge in robotics. The main problem is to find an appropriate grasp configuration including the position and orientation of the arm relative to the object and fingers configuration. One approach is to recognize an appropriate grasp pose for an object based on one or more grasp demonstrations of the same or other objects. We focus on...
Three-dimensional object detection and recognition is increasingly in manipulation and navigation applications in autonomous service robots. It involves clustering points of the point cloud from an unstructured scene into objects candidates and estimating features to recognize the objects under different circumstances such as occlusions and clutter. This paper presents an efficient approach capable...
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