Grasping unknown objects by exploiting shape adaptability and environmental constraints

In grasping, shape adaptation between hand and object has a major influence on grasp success. In this paper, we present an approach to grasping unknown objects that explicitly considers the effect of shape adaptability to simplify perception. Shape adaptation also occurs between the hand and the environment, for example, when fingers slide across the surface of the table to pick up a small object. Our approach to grasping also considers environmental shape adaptability to select grasps with high probability of success. We validate the proposed shape-adaptability-aware grasping approach in 880 real-world grasping trials with 30 objects. Our experiments show that the explicit consideration of shape adaptability of the hand leads to robust grasping of unknown objects. Simple perception suffices to achieve this robust grasping behavior.

Authors

• Clemens Eppner
• Oliver Brock

Keywords

• Shape
• Grasping
• Robustness
• Adaptation models
• Image segmentation
• Robot sensing systems
• Solid modeling
• Environmental Constraints
• Unknown Objects
• Shape Adaptation
• Small Objects
• High Probability Of Success
• Goodness Of Fit
• Size Ratio
• Depth Images
• Geometric Model
• Object Shape
• Contact Force
• Objects In The Scene
• Segment Size
• Shape Descriptors
• Random Sample Consensus
• Curvilinear Coordinates
• Robotic Hand