4 results about "Tactile Perceptions" patented technology

The application discloses a kind of dexterous hand's negative pressure tactile perception system and perception method, characterized by including vacuum pump and primary pressure measuring air path, each finger of dexterous hand is provided with vacuum perception port on each finger joint, each vacuum perception port is connected with three-stage pressure measuring air path by flexible air pipe, the three-stage pressure measuring air path connected with the vacuum perception port on the same finger is connected with the same secondary pressure measuring air path, all secondary pressure measuring air paths are connected with primary pressure measuring air path;Advantages are that the negative pressure tactile perception system can install each pressure measuring air path in the arm of robot, and is connected to the vacuum perception port of finger joint through flexible air pipe, so that the air pressure sensor for pressure measurement is away from dexterous hand, avoids being affected by the cold or magnetic field of contact object, and ensures the accuracy of tactile perception.

The application discloses a kind of dexterous hand's negative pressure tactile perception system and perception method, characterized by including vacuum pump and primary pressure measuring air path, each finger of dexterous hand is provided with vacuum perception port on each finger joint, each vacuum perception port is connected with three-stage pressure measuring air path by flexible air pipe, the three-stage pressure measuring air path connected with the vacuum perception port on the same finger is connected with the same secondary pressure measuring air path, all secondary pressure measuring air paths are connected with primary pressure measuring air path;Advantages are that the negative pressure tactile perception system can install each pressure measuring air path in the arm of robot, and is connected to the vacuum perception port of finger joint through flexible air pipe, so that the air pressure sensor for pressure measurement is away from dexterous hand, avoids being affected by the cold or magnetic field of contact object, and ensures the accuracy of tactile perception.

The application provides an object attribute perception method and device based on dexterous hand touch and a storage medium, and belongs to the technical field of touch perception. The method comprises the following steps: controlling a dexterous hand provided with a three-dimensional force sensor array to perform initial light touch scanning on a target object, and acquiring preliminary profile information of the target object; determining a key region of the surface of the target object based on the preliminary profile information, wherein the key region comprises a high-curvature region and / or a flat region; determining a corresponding perception strategy according to the type of the key region; and controlling the dexterous hand to perform the corresponding perception strategy in the key region, and acquiring a physical attribute perception result. The application can adapt to object characteristics and collaboratively perceive multiple attributes of the object.

The application discloses a wood material tactile subjective perception prediction method, which comprises the following steps: step one, preparing a wood material sample set, collecting subjective scores of wood material samples in the dimensions of smoothness, roughness, stickiness and softness, and constructing a tactile subjective perception database; step two, collecting surface images of the wood material samples and vibration signals generated by fingers rubbing the surfaces, and extracting visual features and tactile features from the surface images and the vibration signals respectively. The wood material tactile subjective perception prediction method provided by the application fuses visual and tactile multi-scale features, constructs a fine-grained feature system to improve prediction accuracy, introduces a finishing gate variable to adaptively distinguish different surface states and enhance the model generalization ability, then adopts high-dimensional feature robust processing and elastic net regularization to effectively inhibit small sample overfitting, and finally ensures the model robustness and prediction reliability.