为了实现消防灭火机器人在工业园区自主行走与智能灭火,研发了一款具有良好应用前景的智能消防灭火机器人。根据机器人性能要求,明确了其主要结构与工作原理,完成了机器人结构设计、控制系统搭建与行走动力学建模。结合载波相位差分的...为了实现消防灭火机器人在工业园区自主行走与智能灭火,研发了一款具有良好应用前景的智能消防灭火机器人。根据机器人性能要求,明确了其主要结构与工作原理,完成了机器人结构设计、控制系统搭建与行走动力学建模。结合载波相位差分的实时动态(Real time kinematic,RTK)和同时定位与建图(Simultaneous localization and mapping,SLAM)技术实现了机器人自主导航与定位功能,在开发机器人自主火源探测与定向技术的基础上提出并实现了机器人智能灭火的新方法。试验结果表明,所研发的智能消防灭火机器人能在工业园区自主行走、自主寻找火源与智能灭火,其行走速度大于0.4 m/s,定位误差小于0.4 m,火源识别率大于90%。展开更多
For the purpose of study on forecasting forest fire behavior,a probability approach was presented to search ignition sources by multi-robot coordination. Firstly,the environment map is built based on Bayes rules. Then...For the purpose of study on forecasting forest fire behavior,a probability approach was presented to search ignition sources by multi-robot coordination. Firstly,the environment map is built based on Bayes rules. Then,the probability searching strategy based on the environment map was designed. Every grid of the searching area was assigned searching expectation value, and robots selected the grid with the highest expectation value as its searching target. The simulation results show the search time reduces greatly,which proves the feasibility and validity of the given algorithm under unknown fire condition.展开更多
文摘为了实现消防灭火机器人在工业园区自主行走与智能灭火,研发了一款具有良好应用前景的智能消防灭火机器人。根据机器人性能要求,明确了其主要结构与工作原理,完成了机器人结构设计、控制系统搭建与行走动力学建模。结合载波相位差分的实时动态(Real time kinematic,RTK)和同时定位与建图(Simultaneous localization and mapping,SLAM)技术实现了机器人自主导航与定位功能,在开发机器人自主火源探测与定向技术的基础上提出并实现了机器人智能灭火的新方法。试验结果表明,所研发的智能消防灭火机器人能在工业园区自主行走、自主寻找火源与智能灭火,其行走速度大于0.4 m/s,定位误差小于0.4 m,火源识别率大于90%。
基金Sponsored by the Fundamental Research Funds for the Central Universities of China(Grant No.DL12BB11)Program for New Century Excellent Talentsin University(Grant No.NCET-10-0279)Heilongjiang Province Postdoctoral Foundation(Grant No.LRB11-334)
文摘For the purpose of study on forecasting forest fire behavior,a probability approach was presented to search ignition sources by multi-robot coordination. Firstly,the environment map is built based on Bayes rules. Then,the probability searching strategy based on the environment map was designed. Every grid of the searching area was assigned searching expectation value, and robots selected the grid with the highest expectation value as its searching target. The simulation results show the search time reduces greatly,which proves the feasibility and validity of the given algorithm under unknown fire condition.
