第6期 曹鹏飞,等:面向多机器人动态任务分配的事件驱动免疫网络算法 ·957· ics and automation,1998.14(2):220-240 [S]许建豪.云计算中基于拍卖的虚拟机动态供应和分配算 法.重庆邮电大学学报:自然科学版,2016,28(4): 585-592 XU Jianhao.Virtual machine dynamic supply and alloca- tion algorithm based on auction in cloud computing[J]. Journal of Chongqing university of posts and telecommu- nications:natural science edition,2016,28(4):585-592. [6]袁明新,叶兆莉,程帅,等.干扰素调节的多机器人协作 (b)机器人系统图2 搬运免疫网络算法).智能系统学报,2014,91):76-82 图4实际机器人系统仿真图 YUAN Mingxin,YE Zhaoli,CHENG Shuai,et al.Multi- Fig.4 Actual robot system simulation robot cooperative handling based on immune network al- 经过多次实验,设置不同任务,系统都能快速 gorithm regulated by interferon[J].CAAI transactions on 反应,激励相应的机器人进行任务的执行与协 intelligent systems,2014,9(1):76-82. 作,验证了文中算法在实际多机器人动态任务分 [7]袁明新,李平正,江亚峰,等.基于胸腺肽调节机制的多 机器人免疫任务分配[.模式识别与人工智能,2014, 配系统中具有较高的可行性。 27(5):472-479. 4结束语 YUAN Mingxin,LI Pingzheng,JIANG Yafeng,et al.Im- mune task allocation for multi-robot system based on ad- 针对一类复杂的松散型动态任务,文中基于 justment mechanism of thymic peptide[J].Pattern recogni- 免疫网络和事件驱动机制,提出一种动态任务分 tion and artificial intelligence,2014,27(5):472-479. 配算法,解决了多机器人的动态任务分配与自主 [8]丁永生.基于生物网络的智能控制与优化研究进展 协作问题,并利用焦躁模型解决了任务分配过程 控制工程,2010,17(4):416-421,536 中的死锁问题,仿真和实验表明本文算法在一类 DING Yongsheng.Research development of bio-network 需要协作的动态任务分配问题中的有效性,具有 based intelligent control and optimization[J].Control en- gineering of China,2010,17(4):416-421,536 较强的自适应性。将文中算法应用于实际场景的 [9]丁永生.计算智能的新框架:生物网络结构).智能系统 多机器人系统中,取得了较好的效果,表明将本 学报,2007,2(2:26-30. 文算法应用到实际的多机器人系统中有较高的可 DING Yongsheng.A new scheme for computational intel- 行性。课题后续将把重点放在分配模型的优化和 ligence:bio-network architecture[J].CAAI transactions on 实际应用的拓展上,在提高算法性能的同时,能 intelligent systems,2007,2(2):26-30. 够实现更大的实际价值。 [10]靳明双,郜帅,张宏科.智慧协同网络研究进展重庆 邮电大学学报:自然科学版,2018,30(1)少22-32. 参考文献: JIN Mingshuang,GAO shuai,ZHANG Hongke.Re- [1]TAVASOLI A,EGHTESAD M,JAFARIAN H.Two-time search progress of smart collaborative identifier networks scale control and observer design for trajectory tracking of [J].Journal of Chongqing university of posts and telecom- two cooperating robot manipulators moving a flexible munications:natural science edition,2018,30(1):22-32. beam[J].Robotics and autonomous systems,2009,57(2): [11]JERNE N K.Towards a network theory of the immune 212-221 system[J].Annales d'immunologie,1974,125(1/2): [2]DAHL T S,MATARIC M,SUKHATME G S.Multi-ro- 373-389. bot task allocation through vacancy chain scheduling[J]. [12]FARMER J D.,PACKARD N H,PERELSON A S.The Robotics and autonomous system,2009,57(6/7):674-687. immune system,adaptation,and machine learning[J]. [3]ZHOU Pucheng,HONG Bingrong,WANG Yuehai,et al. Physica D:nonlinear phenomena,1986,22(1/2/3): Multi-agent cooperative pursuit based on extended con- 187-204 tract net protocol[C]//Proceeding of 2004 International [13]陈蕊,丁永生,郝矿荣.基于事件驱动的动态免疫分簇 Conference on Machine Learning and Cybernetics.Shang- 路由算法[J].计算机应用研究,2016,33(7):2087- hai,China.,2004:169-173. 2090,2109. [4]PARKER L E.ALLIANCE:an architecture for fault toler- CHEN Rui,DING Yongsheng,HAO Kuangrong.Event- ant multirobot cooperation[J].IEEE transactions on robot- driven dynamic immune clustering routing algorithm[J].(b) 机器人系统图 2 图 4 实际机器人系统仿真图 Fig. 4 Actual robot system simulation 经过多次实验,设置不同任务,系统都能快速 反应,激励相应的机器人进行任务的执行与协 作,验证了文中算法在实际多机器人动态任务分 配系统中具有较高的可行性。 4 结束语 针对一类复杂的松散型动态任务,文中基于 免疫网络和事件驱动机制,提出一种动态任务分 配算法,解决了多机器人的动态任务分配与自主 协作问题,并利用焦躁模型解决了任务分配过程 中的死锁问题,仿真和实验表明本文算法在一类 需要协作的动态任务分配问题中的有效性,具有 较强的自适应性。将文中算法应用于实际场景的 多机器人系统中,取得了较好的效果,表明将本 文算法应用到实际的多机器人系统中有较高的可 行性。课题后续将把重点放在分配模型的优化和 实际应用的拓展上,在提高算法性能的同时,能 够实现更大的实际价值。 参考文献: TAVASOLI A, EGHTESAD M, JAFARIAN H. Two-time scale control and observer design for trajectory tracking of two cooperating robot manipulators moving a flexible beam[J]. Robotics and autonomous systems, 2009, 57(2): 212–221. [1] DAHL T S, MATARIC M, SUKHATME G S. Multi-robot task allocation through vacancy chain scheduling[J]. Robotics and autonomous system, 2009, 57(6/7): 674–687. [2] ZHOU Pucheng, HONG Bingrong, WANG Yuehai, et al. Multi-agent cooperative pursuit based on extended contract net protocol[C]//Proceeding of 2004 International Conference on Machine Learning and Cybernetics. Shanghai, China, 2004: 169–173. [3] PARKER L E. ALLIANCE: an architecture for fault tolerant multirobot cooperation[J]. IEEE transactions on robot- [4] ics and automation, 1998, 14(2): 220–240. 许建豪. 云计算中基于拍卖的虚拟机动态供应和分配算 法 [J]. 重庆邮电大学学报: 自然科学版, 2016, 28(4): 585–592. XU Jianhao. Virtual machine dynamic supply and allocation algorithm based on auction in cloud computing[J]. Journal of Chongqing university of posts and telecommunications: natural science edition, 2016, 28(4): 585–592. [5] 袁明新, 叶兆莉, 程帅, 等. 干扰素调节的多机器人协作 搬运免疫网络算法 [J]. 智能系统学报, 2014, 9(1): 76–82. YUAN Mingxin, YE Zhaoli, CHENG Shuai, et al. Multirobot cooperative handling based on immune network algorithm regulated by interferon[J]. CAAI transactions on intelligent systems, 2014, 9(1): 76–82. [6] 袁明新, 李平正, 江亚峰, 等. 基于胸腺肽调节机制的多 机器人免疫任务分配 [J]. 模式识别与人工智能, 2014, 27(5): 472–479. YUAN Mingxin, LI Pingzheng, JIANG Yafeng, et al. Immune task allocation for multi-robot system based on adjustment mechanism of thymic peptide[J]. Pattern recognition and artificial intelligence, 2014, 27(5): 472–479. [7] 丁永生. 基于生物网络的智能控制与优化研究进展 [J]. 控制工程, 2010, 17(4): 416–421, 536. DING Yongsheng. Research development of bio-network based intelligent control and optimization[J]. Control engineering of China, 2010, 17(4): 416–421, 536. [8] 丁永生. 计算智能的新框架: 生物网络结构 [J]. 智能系统 学报, 2007, 2(2): 26–30. DING Yongsheng. A new scheme for computational intelligence: bio-network architecture[J]. CAAI transactions on intelligent systems, 2007, 2(2): 26–30. [9] 靳明双, 郜帅, 张宏科. 智慧协同网络研究进展 [J]. 重庆 邮电大学学报: 自然科学版, 2018, 30(1): 22–32. JIN Mingshuang, GAO shuai, ZHANG Hongke. Research progress of smart collaborative identifier networks [J]. Journal of Chongqing university of posts and telecommunications: natural science edition, 2018, 30(1): 22–32. [10] JERNE N K. Towards a network theory of the immune system[J]. Annales d’immunologie, 1974, 125(1/2): 373–389. [11] FARMER J D, PACKARD N H, PERELSON A S. The immune system, adaptation, and machine learning[J]. Physica D: nonlinear phenomena, 1986, 22(1/2/3): 187–204. [12] 陈蕊, 丁永生, 郝矿荣. 基于事件驱动的动态免疫分簇 路由算法 [J]. 计算机应用研究, 2016, 33(7): 2087– 2090, 2109. CHEN Rui, DING Yongsheng, HAO Kuangrong. Eventdriven dynamic immune clustering routing algorithm[J]. [13] 第 6 期 曹鹏飞,等:面向多机器人动态任务分配的事件驱动免疫网络算法 ·957·