Abstract：In the computer vision research, simultaneous localization and mapping (SLAM) is one of the most challenging problems. The ACP theory provides a new and e ective solution for modeling and control of complex systems. In the proposed parallel perception and its basic framework and key techniques, the ACP theory is innovatively introduced into the SLAM algorithm. For parallel perception, artificial scenes are used to represent complex real scene, computational experiments are used to train and evaluate models and parameters of visual SLAM algorithms, and parallel execution aims to continuously optimize the vision system and achieve the intelligent perception and understanding of complex systems. As a result, a novel and new perception theory is constructed to integrate low-level vision algorithms and high-level decision and analysis.
引用本文:
孟祥冰，王蓉，张梅，王飞跃. 平行感知: ACP 理论在视觉SLAM 技术中的应用[J]. 指挥与控制学报, 2017, 3(4): 350-358.
MENG Xiang-Bing, WANG Rong, ZHANG Mei, WANG Fei-Yue. Parallel Perception: An ACP-based Approach to Visual SLAM. Journal of Command and Control, 2017, 3(4): 350-358.
2017, Vol. 3 
