摘要
为了支持未知环境下移动机器人自主导航,提出了移动机器人的并行免疫计算模型,为解决其在线导航优化、病毒/路障识别和计算效率问题提供了基础组织。免疫计算模型分为固有免疫计算层、适应性免疫计算层和并行/分布式计算层,并行免疫计算模型建立在此3个免疫计算模型基础上。探讨了移动机器人并行免疫计算模型的负载极限和负载平衡,分析了此类移动机器人系统的鲁棒性;提出了移动机器人并行免疫计算模型用于路障识别的方法。移动机器人并行免疫计算模型的复杂性分析及仿真结果表明,并行计算能提高其效率;仿真结果表明,移动机器人可消除病毒,并具有较高计算性能。
To support the autonomous navigation of mobile robot in unknown environment, parallel immune computation model was proposed, and the infrastructure for solving the problems of optimization, recognition and efficiency in online robot navigation was provided. Immune computation model is comprised of inherent immune computation tier, adaptive immune computation tier and parallel / distributed computation tier, and the parallel immune computation（PIC） model is built based on the tri-tier immune computation model. The load threshold and load balance of the PIC model of the mobile robot were discussed, robustness of the mobile robot system was analyzed, and the obstacle recognition method based on the PIC model was proposed. According to the results from complexity analysis of PIC model show that parallel computation increases the efficiency of mobile robot. And the simulation results show that the mobile robot can eliminate viruses and computing performance of the mobile robot is good.
出处
《中南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2006年第1期124-129,共6页
Journal of Central South University:Science and Technology
基金
国家自然科学基金重点资助项目(60234030)
国家自然科学基金资助项目(60404021)
关键词
移动机器人
并行免疫计算
效率
模式识别
复杂性
mobile robot
parallel immune computation
efficiency
pattern recognition
complexity
