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机构地区:[1]广东工业大学可拓学与创新方法研究所,广东广州510006 [2]广东工业大学机电工程学院,广东广州510006
出 处:《广东工业大学学报》2016年第4期1-6,共6页Journal of Guangdong University of Technology
基 金:国家自然科学基金资助项目(61273306);广东省科技计划项目(2016A040404015)
摘 要:智能识别障碍物是无人车的必备技术,目前对该技术的研究已经成为热门的研究方向.本文依据可拓学的基本理论与方法,从解决矛盾问题的角度对可拓识别方法进行了深入研究,给出了定性与定量相结合的可拓识别方法的一般步骤和流程,并将该方法应用于无人车识别障碍物,获得了符合识别要求的策略,证明了其可行性.该方法也为研制可拓识别系统提供了思路,具有广阔的应用前景.Intelligent obstacle recognition is the essential technology of the self-driving car, which has been a popular research so far. Based on the basic theory and method of Extenics, a research is carried out by using the extension recognition method, to solve contradictory problems. The general procedure of extension recognition method is provided, combining qualitative analysis with quantitative calculation. This method is applied on obstacle recognition of the self-driving car and a strategy obtained that conform to the recognition requirements. The case analysis proves the feasibility of this method. In the meantime, this method offers a research idea for the development of extension recognition system and has a broad ap-plication prospect.
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