智能优化算法研究及其在移动机器人相关技术中的应用
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摘要
移动机器人的研究始于上世纪60年代末期,移动机器人是典型的自主式智能系统,是高技术领域中的一个热点,是计算机人工智能、机器人学、控制理论和电子技术等多个技术学科交叉的产物,不仅有着潜在的十分诱人的应用价值和商业价值,而且对它的研究本身也是对智能化技术的挑战,使移动机器人的发展为各种智能化技术和方案的研究提供了优良的试验平台。目前,虽然对移动机器人相关技术的研究已取得了大量的成果,但还有很多关键理论和实际问题有待解决和完善。因此,进行移动机器人相关技术的研究,实现移动机器人的全智能化具有实际意义。目前的研究表明,要研制出在未知或复杂的变化环境下全自主式的移动机器人尚不可能,但在移动机器人智能化的过程中,人机交互也随之智能化。进入二十世纪九十年代,以研制高水平的环境信息传感器、信息处理技术、高适应性的移动机器人控制技术和真实环境下的规划技术为标志,展开了移动机器人更高层次的研究。
本文以移动机器人的建模与仿真、路径规划、传感器信息融合为研究任务,主要研究与移动机器人相关技术的智能优化算法及应用。移动机器人相关技术主要是指:静态的或者变化的已知、部分己知和未知环境下移动机器人路径规划的理论、方法与关键技术;环境建模与定位方法;与移动机器人相关的智能算法的基础理论与实现方法,主要的研究内容为:
1.在研究遗传算法、免疫算法、克隆选择算法以及量子算法等智能优化算法的基础上,着重研究了这些智能优化算法的混合,对免疫遗传算法、免疫克隆选择算法及量子遗传算法进行了算法设计与收敛性分析,通过算例仿真得知,混合的智能优化算法优于单一算法,具有很强的鲁棒性,寻优速度快,收敛性强等特点。
2.对多传感器信息融合的方法、结构和层次进行了深入的分析和比较,采用自适应加权融合算法,实现基于超声波传感器和红外传感器信息的融合,使移动机器人能自主避障和导航。
3.通过建立轮式自主运行移动机器人的运动学和动力学模型,获得其位置、速度的表达式,分析其能控性和稳定性,采用遗传算法对移动机器人的PID参数进行整定,以实现对移动机器人运动的精确控制。同时对移动机器人系统总体结构和各子系统模型进行了设计。
4.着重研究了遗传算法、量子遗传算法、免疫算法以及免疫克隆算法等智能优化算法在移动机器人路径规划中的应用与实现,以解决移动机器人在动态和非结构环境下路径规划的难题。
The study of the mobile robot began in the late 1960s. The mobile robot is typical autonomous intelligent system, is a hot of the high-tech field, is the cross-product of the computer artificial intelligence, robotics, control theory, electronic technology and other technical disciplines. Not only is the mobile robot very attractive value and commercial value, but it is also the challenge of the study of intelligent technology which makes the development of the mobile robot provide a good test platform for the study of various intelligent technology and programs. Now, the related studies of the mobile robot technology have made a lot of achievements, but there are many key theoretical and technical issues to be addressed and improved. Thus, mobile machinery-related technology and mobile intelligent robots are all very practical significance. Under the unknown or complicated environment, current research shows that it is not yet possible to design autonomous mobile robot. In the process of the intelligent of the mobile robot, HCI are also intelligence. In 1990s, with the sign of high standards of environmental information sensors, information technology, high adaptability of mobile robot control technology and real environment for the planning of technical signs, it launched a higher level research of mobile robot.
In this dissertation, for the study assignment of the based mobile robot modeling and simulation, path planning, sensor data fusion for research, the main assignment is the application of intelligent optimization algorithms. Mobile robot-related technologies means: Static or change known, some known and unknown environment mobile robot path planning theories, methodologies and key technologies; environmental modeling and orientation methods; intelligent algorithm of the theory and methods related with mobile robot based and so on, master reserch content is:
1. On the basis of researching genetic algorithm, immune algorithm, clonal selection algorithm and quantum algorithm as well as intelligent optimization algorithm, focusing on the intelligent optimization algorithm mixed, the immune genetic algorithm and immune clonal selection algorithm and quantum algorithm for genetic algorithm design and analysis of convergence, the algorithm proved that Hybrid Intelligent optimization algorithm is better than a single algorithm, and it is very robust , fast optimization, convergence so on.
2. We analyze and compare the multi-sensor information fusion method, structure and levels. Adaptive weighted fusion algorithm based ultrasonic sensor and infrared sensor information fusion can enable autonomous mobile robot obstacle avoidance and navigation
3. Through modeling of wheeled mobile robot kinematics and dynamics model, we get its expression of location and speed and analyze its controllability and stability. A genetic algorithm was used to the adjustment of PID parameters of the mobile robot and designs the architecture of the mobile robot system and the models of the subsystem.
4. We study the implementation and application of genetic algorithms, quantum genetic algorithm, immune algorithm and immune clonal algorithm in mobile robot path planning so as to solve the path planning problem of mobile robots in dynamic and non-structural environment.
本文以移动机器人的建模与仿真、路径规划、传感器信息融合为研究任务,主要研究与移动机器人相关技术的智能优化算法及应用。移动机器人相关技术主要是指:静态的或者变化的已知、部分己知和未知环境下移动机器人路径规划的理论、方法与关键技术;环境建模与定位方法;与移动机器人相关的智能算法的基础理论与实现方法,主要的研究内容为:
1.在研究遗传算法、免疫算法、克隆选择算法以及量子算法等智能优化算法的基础上,着重研究了这些智能优化算法的混合,对免疫遗传算法、免疫克隆选择算法及量子遗传算法进行了算法设计与收敛性分析,通过算例仿真得知,混合的智能优化算法优于单一算法,具有很强的鲁棒性,寻优速度快,收敛性强等特点。
2.对多传感器信息融合的方法、结构和层次进行了深入的分析和比较,采用自适应加权融合算法,实现基于超声波传感器和红外传感器信息的融合,使移动机器人能自主避障和导航。
3.通过建立轮式自主运行移动机器人的运动学和动力学模型,获得其位置、速度的表达式,分析其能控性和稳定性,采用遗传算法对移动机器人的PID参数进行整定,以实现对移动机器人运动的精确控制。同时对移动机器人系统总体结构和各子系统模型进行了设计。
4.着重研究了遗传算法、量子遗传算法、免疫算法以及免疫克隆算法等智能优化算法在移动机器人路径规划中的应用与实现,以解决移动机器人在动态和非结构环境下路径规划的难题。
The study of the mobile robot began in the late 1960s. The mobile robot is typical autonomous intelligent system, is a hot of the high-tech field, is the cross-product of the computer artificial intelligence, robotics, control theory, electronic technology and other technical disciplines. Not only is the mobile robot very attractive value and commercial value, but it is also the challenge of the study of intelligent technology which makes the development of the mobile robot provide a good test platform for the study of various intelligent technology and programs. Now, the related studies of the mobile robot technology have made a lot of achievements, but there are many key theoretical and technical issues to be addressed and improved. Thus, mobile machinery-related technology and mobile intelligent robots are all very practical significance. Under the unknown or complicated environment, current research shows that it is not yet possible to design autonomous mobile robot. In the process of the intelligent of the mobile robot, HCI are also intelligence. In 1990s, with the sign of high standards of environmental information sensors, information technology, high adaptability of mobile robot control technology and real environment for the planning of technical signs, it launched a higher level research of mobile robot.
In this dissertation, for the study assignment of the based mobile robot modeling and simulation, path planning, sensor data fusion for research, the main assignment is the application of intelligent optimization algorithms. Mobile robot-related technologies means: Static or change known, some known and unknown environment mobile robot path planning theories, methodologies and key technologies; environmental modeling and orientation methods; intelligent algorithm of the theory and methods related with mobile robot based and so on, master reserch content is:
1. On the basis of researching genetic algorithm, immune algorithm, clonal selection algorithm and quantum algorithm as well as intelligent optimization algorithm, focusing on the intelligent optimization algorithm mixed, the immune genetic algorithm and immune clonal selection algorithm and quantum algorithm for genetic algorithm design and analysis of convergence, the algorithm proved that Hybrid Intelligent optimization algorithm is better than a single algorithm, and it is very robust , fast optimization, convergence so on.
2. We analyze and compare the multi-sensor information fusion method, structure and levels. Adaptive weighted fusion algorithm based ultrasonic sensor and infrared sensor information fusion can enable autonomous mobile robot obstacle avoidance and navigation
3. Through modeling of wheeled mobile robot kinematics and dynamics model, we get its expression of location and speed and analyze its controllability and stability. A genetic algorithm was used to the adjustment of PID parameters of the mobile robot and designs the architecture of the mobile robot system and the models of the subsystem.
4. We study the implementation and application of genetic algorithms, quantum genetic algorithm, immune algorithm and immune clonal algorithm in mobile robot path planning so as to solve the path planning problem of mobile robots in dynamic and non-structural environment.
引文
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