Paper
27 March 1989 A Multi-Sensor Robotics System For Object Recognition
Khosrow M. Hassibi, Kenneth A. Loparo, Francis L. Merat
Author Affiliations +
Proceedings Volume 1002, Intelligent Robots and Computer Vision VII; (1989) https://doi.org/10.1117/12.960283
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States
Abstract
An algorithm for object recognition based on the data from various contact and/or non-contact sensors is described. The sensors are primarily used for resolving the ambiguities which may be encountered in recognizing the object identity and its pose. The feature vector representing an object-state is partitioned into a finite number of feature subvectors each containing the features extracted from a different sensory source. To perform the recognition task through integration of data from different sensors, an a priori cost value is assigned to each feature. These feature costs and the object models are used for deriving a decision tree based on a sequential pattern, recognition approach. The decision tree guides the system during the recognition phase. General strategies for feature extraction from various sources are implemented as a finite state machine. A coordinator module supervises the coordination of manipulation and recognition processes and the execution of system state changes which are required to successfully implement the recognition algorithm.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Khosrow M. Hassibi, Kenneth A. Loparo, and Francis L. Merat "A Multi-Sensor Robotics System For Object Recognition", Proc. SPIE 1002, Intelligent Robots and Computer Vision VII, (27 March 1989); https://doi.org/10.1117/12.960283
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KEYWORDS
Sensors

Detection and tracking algorithms

Object recognition

Robot vision

Feature extraction

Distance measurement

Pattern recognition

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