Haptic classification of common objects: Knowledge-driven exploration
Identifieur interne : 00A207 ( Main/Merge ); précédent : 00A206; suivant : 00A208Haptic classification of common objects: Knowledge-driven exploration
Auteurs : Susan J. Lederman ; Roberta L. Klatzky [États-Unis]Source :
- Cognitive Psychology [ 0010-0285 ] ; 1989.
Abstract
In Experiment 1, haptically available object properties that would be diagnostic for constrained common object classification at the basic and subordinate levels were elicited in a questionnaire. The results are considered in terms of the nature of the haptically derived representations of common objects. Initial data are also presented regarding knowledge of the natural co-occurrence of properties in haptic object perception. In Experiment 2, the hand movements executed during haptic classification of manipulable common objects were examined. Manual exploration consisted of a two-stage sequence, an initial generalized “grasp-and-lift” routine, followed by a series of more specialized hand-movement patterns strongly driven by knowledge of the property diagnosticity for the specific object (obtained in Experiment 1). The current results may guide computational models of human haptic object classification and the development of perceptual systems for robots equipped with sensate dextrous hands, capable of intelligent exploration, recognition, and manipulation of concrete objects.
Url:
DOI: 10.1016/0010-0285(90)90009-S
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<front><div type="abstract" xml:lang="en">In Experiment 1, haptically available object properties that would be diagnostic for constrained common object classification at the basic and subordinate levels were elicited in a questionnaire. The results are considered in terms of the nature of the haptically derived representations of common objects. Initial data are also presented regarding knowledge of the natural co-occurrence of properties in haptic object perception. In Experiment 2, the hand movements executed during haptic classification of manipulable common objects were examined. Manual exploration consisted of a two-stage sequence, an initial generalized “grasp-and-lift” routine, followed by a series of more specialized hand-movement patterns strongly driven by knowledge of the property diagnosticity for the specific object (obtained in Experiment 1). The current results may guide computational models of human haptic object classification and the development of perceptual systems for robots equipped with sensate dextrous hands, capable of intelligent exploration, recognition, and manipulation of concrete objects.</div>
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