共查询到20条相似文献,搜索用时 156 毫秒
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针对双轮自平衡机器人的运动控制,设计了区间二型模糊逻辑控制器(T2FLC),提出函数融合的方法,解决模糊控制器规则繁杂的问题.首先对双轮机器人进行运动学建模,针对机器人的数学模型,设计双闭环二型模糊自适应PID控制器,分别控制机器人的直立平衡和行走速度.将机器人的反馈变量进行函数融合,简化T2FLC的模糊规则.对设计的... 相似文献
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基于FPSO的电力巡检机器人的广义二型模糊逻辑控制 总被引:1,自引:1,他引:0
针对电力巡检机器人(Power-line inspection robot, PLIR)的平衡调节问题, 设计了广义二型模糊逻辑控制器(General type-2 fuzzy logic controller, GT2FLC); 针对GT2FLC中隶属函数参数难以确定的问题, 通过模糊粒子群(Fuzzy particle swarm optimization, FPSO)算法来优化隶属函数参数. 将GT2FLC的控制性能与区间二型模糊逻辑控制器(Interval type-2 fuzzy logic controller, IT2FLC)和一型模糊逻辑控制器(Type-1 fuzzy logic controller, T1FLC) 的控制性能进行对比. 除此之外, 还考虑了外部干扰对三种控制器控制效果的影响. 仿真结果表明, GT2FLC具有更好的性能和处理不确定性的能力. 相似文献
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以两轮移动机器人(TWMR)为对象,针对机器人的非线性模型分别设计控制机器人平衡和位置的区间二型模糊逻辑控制器(IT2 FLC).针对区间二型模糊规则中参数难以设定的问题,通过改进的量子粒子群算法(LTQPSO)优化区间二型模糊集参数,并给出优化算法的流程图.针对区间二型模糊逻辑控制器和一型模糊逻辑控制器(T1 FLC)对平衡和位置的控制效果进行对比.进一步考虑质量不确定和位置扰动对两种控制器控制效果的影响.仿真结果表明,IT2 FLC可以有效地达到设定的控制目标,与T1 FLC相比,IT2 FLC拥有更好的处理不确定性的能力以及更强的抗扰动能力. 相似文献
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借鉴内分泌系统对神经系统与遗传系统的高层调节机制,提出了一种新的基于内分泌调节机制的机器人行为规划算法.此算法中机器人通过神经系统接受环境信息并进行行为决策,行为决策的效果通过一种情感学习模型进行反馈.情感学习模型根据机器人的内、外环境状态,产生情感因子(即生物激素),再由情感因子来调节神经系统的记忆和行为决策,最后神经系统的记忆与行为模式又由遗传系统得以继承.该算法有效避免了神经系统复杂的自学习过程。同时也保证机器人有较强的自适应能力.为了验证算法的有效性,本文做了机器人足球队守门员训练的仿真实验,结果也表明该算法具有很强的自适应学习能力. 相似文献
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四腿机器人步态参数自动进化研究与实现 总被引:3,自引:0,他引:3
采用进化算法和基于自主视觉的适应度评估方法,实现了四腿机器人在RoboCup机器人足球比赛现场的行走步态在线自动进化.我们引入内推法作为交叉方法,利用PC基站进行进化算法计算和流程主控,并采用了一些学习时间缩减策略.实现了进化学习的连续性和可扩展性,使得学习过程可以在4060min内完成,这样就能在比赛现场对ERS-7四足机器人进行行走再学习,提高了行走控制的适应性.算法最终结果使ERS-7型四足机器人的行走速度从27cm/s提升到43cm/s. 相似文献
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自主机器人的强化学习研究进展 总被引:9,自引:1,他引:8
虽然基于行为控制的自主机器人具有较高的鲁棒性,但其对于动态环境缺乏必要的自
适应能力.强化学习方法使机器人可以通过学习来完成任务,而无需设计者完全预先规定机
器人的所有动作,它是将动态规划和监督学习结合的基础上发展起来的一种新颖的学习方法
,它通过机器人与环境的试错交互,利用来自成功和失败经验的奖励和惩罚信号不断改进机
器人的性能,从而达到目标,并容许滞后评价.由于其解决复杂问题的突出能力,强化学习
已成为一种非常有前途的机器人学习方法.本文系统论述了强化学习方法在自主机器人中的
研究现状,指出了存在的问题,分析了几种问题解决途径,展望了未来发展趋势. 相似文献
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在诸如机器人足球赛等典型的可分解马尔可夫决策过程(factored Markov decision process,简称FMDP)模型中,不同状态属性在不同的状态下,对于状态评估的影响程度是不同的,其中存在若干关键状态属性,能够唯一或近似判断当前状态的好坏.为了解决FMDP模型中普遍存在的“维数灾”问题,在效用函数非线性的情况下,通过对状态特征向量的提取近似状态效用函数,同时根据对FMDP模型的认知程度,从线性规划和再励学习两种求解角度分别进行约束不等式组的化简和状态效用函数的高维移植,从而达到降低计算复杂度,加快联合策略生成速度的目的、以机器人足球赛任意球战术配合为背景进行实验来验证基于状态特征向量的再励学习算法的有效性和学习结果的可移植性.与传统再励学习算法相比,基于状态特征向量的再励学习算法能够极大地加快策略的学习速度.但更重要的是,还可以将学习到的状态效用函数方便地移植到更高维的FMDP模型中,从而直接计算出联合策略而不需要重新进行学习. 相似文献
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《Advanced Robotics》2013,27(1):37-50
MAPS (Multi-Agent Planning System) is a system for multi-agent coordination that has been developed in the robot soccer domain. It uses potential fields to model the environment and provide directives for the robots. The key feature that enables successful coordination is the use of a shared world model. This paper describes MAPS and demonstrates it as a viable coordination system for use in multiple robot domains. 相似文献
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In order to solve most of the existing mobile robotics applications, the robot needs some information about its spatial environment encoded in what it has been commonly called a map. The knowledge contained in such a map, whatever approach is used to obtain it, will mainly be used by the robot to gain the ability to navigate in a given environment. We are describing in this paper, a method that allows a robot or team of robots to navigate in large urban areas for which an existing map in a standard human understandable fashion is available. As detailed maps of most urban areas already exist, it will be assumed that a map of the zone where the robot is supposed to work is given, which has not been constructed using the robot’s own sensors. We propose in this paper, the use of an existing Geographical Information System based map of an urban zone so that a robot or a team of robots can connect to this map and use it for navigation purposes. Details of the implemented system architecture as well as a position tracking experiment in a real outdoor environment, a University Campus, are provided. 相似文献
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In recent years, the interest in research on robots has increased extensively; mainly due to avoid human to involve in hazardous task, automation of Industries, Defence, Medical and other household applications. Different kinds of robots and different techniques are used for different applications. In the current research proposes the Adaptive Neuro Fuzzy Inference System (ANFIS) Controller for navigation of single as well as multiple mobile robots in highly cluttered environment. In this research it has tried to design a control system which will be able decide its own path in all environmental conditions to reach the target efficiently. Some other requirement for the mobile robot is to perform behaviours like obstacle avoidance, target seeking, speed controlling, knowing the map of the unknown environments, sensing different objects and sensor-based navigation in robot’s environment. 相似文献
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基于专家系统的多移动机器人模糊自校正协调系统 总被引:1,自引:1,他引:1
研究多移动机器人的运动规划问题,在实时运动规划专家系统的基础上提出了一种串级模糊控制器,以校正实际工作环境下各机器人的运动状态与理想情况下可能产生的误差,使各机器人正确调整各自运动状态,达到协调工作的目的。 相似文献
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V. F. Filaretov D. A. Yukhimets 《Journal of Computer and Systems Sciences International》2017,56(4):738-748
This paper addresses the path planning problem for autonomous mobile robots operating in an unknown environment with obstacles. Paths are formed based on third-order Bezier splines and, then, are corrected on the move as a robot detects obstacles with its onboard sensors. During this correction, the initial path between two reference points is divided into two segments (described by Bezier splines) in such a way as to allow the robot to move at a safe distance from a detected obstacle along a smooth resultant trajectory. In this case, the use of smooth paths ensures a high levels of accuracy and velocity of mobile robots during their operation. 相似文献
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规划管理信息系统中的版本管理的研究 总被引:3,自引:0,他引:3
系统分析了规划管理信息系统中版本数据的特点,并对其版本进行了划分,首次提出了基于版本分类的版本管理策略及其版本管理实现技术,通过在基于国产GIS的城市规划管理信息系统中的应用,证明是正确的,增强了规划管理信息系统中版本管理的功能。 相似文献
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针对在有障碍物场地中感知范围受限的群机器人协同围捕问题,本文首先给出了机器人个体、障碍物、目标的模型,并用数学形式对围捕任务进行描述,在此基础上提出了机器人个体基于简化虚拟速度和基于航向避障的自主围捕控制律.基于简化虚拟速度模型的控制律使得机器人能自主地围捕目标同时保持与同伴的距离避免互撞;基于航向的避障方法提升了个体的避障效率,避免斥力避障方法导致的死锁问题.其次本文证明了在该控制律下系统的稳定性.仿真结果表明,该算法在有效围捕目标的同时能够高效地避开障碍物,具有对复杂环境的适应性.最后本文分析了与其他方法相比该算法的优点. 相似文献
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This paper presents an algorithm called augmented Lagrangian particle swarm optimization with velocity limits (VL-ALPSO).
It uses a particle swarm optimization (PSO) based algorithm to optimize the motion planning for swarm mobile robots. Considering
problems with engineering constraints and obstacles in the environment, the algorithm combines the method of augmented Lagrangian
multipliers and strategies of velocity limits and virtual detectors so as to ensure enforcement of constraints, obstacle avoidance
and mutual avoidance. All the strategies together with basic PSO are corresponding to real situations of swarm mobile robots
in coordinated movements. This work also builds a swarm motion model based on Euler forward time integration that involves
some mechanical properties such as masses, inertias or external forces to the swarm robotic system. Simulations show that
the robots moving in the environment display the desired behavior. Each robot has the ability to do target searching, obstacle
avoidance, random wonder, acceleration or deceleration and escape entrapment. So, in summary due to the characteristic features
of the VL-ALPSO algorithm, after some engineering adaptation, it can work well for the planning of coordinated movements of
swarm robotic systems. 相似文献
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Recently, various autonomous mobile robots have been developed for practical use. To support the coexistence of robots and humans in real environments, we propose a concept named ‘Region with Velocity Constraints (RVC),’ which is set around hazardous areas. RVCs are regions where the velocities of the robot are constrained to predefined values. Inside the RVCs, the robot has to reduce its translational velocity to avoid predicted hazards such as collisions with obstacles, and to reduce its rotational velocity to prevent undesirable motions such as sharp turns. We also propose a motion planning method for navigating the mobile robot in an environment with RVCs based on the Navigation Function and Global Dynamic Window Approach. Our method generates a trajectory satisfying both translational and rotational velocity constraints to be compatible with the surroundings. Moreover, to demonstrate the validity of our method, we performed numerical simulations and experiments. 相似文献