Visual Servoing With Trifocal Tensor
Abstract
In this paper, a trifocal tensor-based approach is developed for 6 degrees-of-freedom visual servoing. The trifocal tensor model among the current, desired, and initial views is introduced to describe the geometric relationship. Then, the tensor elements are refined to construct the visual feedback without resorting to explicit estimation of the camera pose. Based on the extracted tensor features, an adaptive controller is designed to drive the camera to a desired pose and compensate for the unknown distance scale factor. Moreover, Lyapunov-based techniques are exploited to analyze the system stability and convergence domain. Simulation results are provided to demonstrate the effectiveness of the developed approach.
Domains
Robotics [cs.RO]
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Visual servoing with trifocal tensor_CDC_manuscript08282018.pdf (568.39 Ko)
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