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作 者:童颖 李梦笑 周亮亮[3] 陈志梅[2] 姬培轩 Tong Ying;Li Mengxiao;Zhou Liangliang;Chen Zhimei;Ji Peixuan
机构地区:[1]三峡水力发电厂,宜昌443000 [2]太原科技大学电子信息工程学院,太原030024 [3]太原重工股份有限公司,太原030024
出 处:《起重运输机械》2024年第18期33-39,共7页Hoisting and Conveying Machinery
基 金:山西省重点研发计划项目(202202020101011);中国长江三峡集团有限公司科研项目资助(Z212302023)。
摘 要:文中针对桥式起重机工作空间的环境信息未知情况下的路径规划,提出了改进人工蜂群算法和滚动规划策略相结合的智能避障路径规划新方法。通过分析并借鉴机器人在未知环境下的路径规划方法,以人工蜂群智能算法为基础,改变蜜源初始化机制以及观察蜂跟随机制,并结合滚动规划策略,提出子目标点选取机制,为了避免起重机多次升降,固定其吊装高度进行局部路径规划。保证了起重机在全局环境信息未知条件下能依据不断更新的窗口信息智能避障安全到达目标点,提高了算法的搜索精度和吊装效率,仿真结果验证了该方案的可行性和有效性。As for the path planning of bridge crane when the environmental information of the workspace is unknown,a new intelligent obstacle avoidance path planning method based on improved artificial bee colony algorithm and rolling planning strategy is proposed.By analyzing and drawing lessons from the path planning method of robot in unknown environment,based on artificial bee colony intelligent algorithm,the mechanism of honey source initialization and observation bee following was changed,and combined with the rolling planning strategy,the sub-target point selection mechanism was proposed,and to avoid the crane lifting many times,the hoisting height was fixed for local path planning,which ensures that the crane can intelligently avoid obstacles and safely reach the target point according to the constantly updated window information under the condition of unknown global environmental information,and improves the search accuracy and hoisting efficiency of the algorithm.The simulation results verify the feasibility and effectiveness of the scheme.
关 键 词:桥式起重机 未知环境 人工蜂群算法(ABC) 滚动规划策略 智能避障
分 类 号:TP24[自动化与计算机技术—检测技术与自动化装置]
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