Extrinsic Line Contact Sensing from Visuo-Tactile Measurements

As robots increasingly interact with unstructured environments, understanding extrinsic contact is crucial for precise manipulation. In particular, estimating the direction vector of an object in contact with an external surface enables tasks such as alignment, insertion, and controlled motion. We propose a novel approach to estimating the direction vector of extrinsic line contact using vision-based tactile sensors. By tracking the relative motion of a grasped object and leveraging kinematic and frictional constraints, the proposed method accurately infers the contact direction without requiring prior geometric information about the object. The system employs a high-resolution tactile sensor and a motion-tracking algorithm to extract object displacement data, which is then transformed into the world frame for robust estimation. Experimental validation with a robotic manipulator demonstrates that the proposed method achieves an overall mean angular error of 8.71°, confirming its effectiveness in real-world applications. This approach enhances robotic perception and manipulation capabilities, making it a reliable solution for tasks that require precise handling of extrinsic line contact, such as assembly, insertion, and surface interaction.