LEARNING
UNCALIBRATED 3D ROBOTIC VISUAL TRACKING BASED ON STEREO VISION
Pan Qie-lu
- 发表年份
- 2000
- 引用次数
- 4
摘要
This paper proposes a new nonlinear visual mapping model for the 3D ro botic visual tracking problem and a novel visual tracking controller is designed based on artificial neural network without explicit external and internal calib ration. Simulation results show that this method can drive the static tracking e rror to zero quickly and keep good robustness and adaptability at the same time. Additionally, the algorithm is very easy to be implemented with low computation al complexity.
关键词
Computer scienceRobustness (evolution)Artificial intelligenceComputer visionComputationAdaptabilityEye trackingTracking (education)Nonlinear systemArtificial neural network
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