alonso_current_2019: Current Research Trends in Robot Grasping and Bin Picking
Current Research Trends in Robot Grasping and Bin Picking
Robot Grasping
Traditional Bin-picking Approaches
Most algorithms rely on segmentation of RGB-D data. 3D object recognition is done by matching 3D data to their known CAD models. Interactive Closest Point can be used to calculate the alignment and best fitting of a cloud of points with respect to a reference CAD model.
A fast voting scheme similar to the Generalized Hough Transform can be used improving the performance of ICP.
Deep Learning Methodologies for Bin Picking
Deep Learning approaches used RGB-D images as input, and are able to predict grasp success and generalize to novel objects.