Model-Based Planning of Sensor Placement and Optical Settings

Roger Y. Tsai; Kostantinos Tarabanis

doi:10.1117/12.969966

1 March 1990 Model-Based Planning of Sensor Placement and Optical Settings

Roger Y. Tsai, Kostantinos Tarabanis

Proceedings Volume 1198, Sensor Fusion II: Human and Machine Strategies; (1990) https://doi.org/10.1117/12.969966
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

Abstract

We present a model-based vision system that automatically plans the placement and optical settings of vision sensors in order to meet certain generic task requirements common to most industrial machine vision applications. From the planned viewpoints, features of interest on an object will satisfy particular constraints in the image. In this work, the vision sensor is a CCD camera equipped with a programmable lens (i.e. zoom lens) and the image constraints considered are: visibility, resolution and field of view. The proposed approach uses a geometric model of the object as well a model of the sensor, in order to reason about the task and the environment. The sensor planning system then computes the regions in space as well as the optical settings that satisfy each of the constraints separately. These results are finally combined to generate acceptable viewing locations and optical settings satisfying all constraints simultaneously. Camera planning experiments are described in which a robot-arm positions the camera at a computed location and the planned optical settings are set automatically. The corresponding scenes from the candidate viewpoints are shown demonstrating that the constraints are indeed satisfied. Other constraints, such as depth of focus, as well as other vision sensors can also be considered resulting in a fully integrated sensor planning system.

Citation Download Citation

Roger Y. Tsai and Kostantinos Tarabanis "Model-Based Planning of Sensor Placement and Optical Settings", Proc. SPIE 1198, Sensor Fusion II: Human and Machine Strategies, (1 March 1990); https://doi.org/10.1117/12.969966

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