Caging Loops in Shape Embedding Space: Theory and Computation
This addresses the challenge of robotic grasping for objects with complex geometry and topology, enabling more robust and adaptable grasp synthesis.
The paper tackles the problem of synthesizing feasible caging grasps for objects by computing Caging Loops in a shape embedding space, decoupling from surface geometry to handle multiple topological holes and tolerate incomplete data, resulting in reliable grasps for complex objects as demonstrated through experiments.
We propose to synthesize feasible caging grasps for a target object through computing Caging Loops, a closed curve defined in the shape embedding space of the object. Different from the traditional methods, our approach decouples caging loops from the surface geometry of target objects through working in the embedding space. This enables us to synthesize caging loops encompassing multiple topological holes, instead of always tied with one specific handle which could be too small to be graspable by the robot gripper. Our method extracts caging loops through a topological analysis of the distance field defined for the target surface in the embedding space, based on a rigorous theoretical study on the relation between caging loops and the field topology. Due to the decoupling, our method can tolerate incomplete and noisy surface geometry of an unknown target object captured on-the-fly. We implemented our method with a robotic gripper and demonstrate through extensive experiments that our method can synthesize reliable grasps for objects with complex surface geometry and topology and in various scales.