共查询到20条相似文献,搜索用时 15 毫秒
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A computationally efficient, obstacle avoidance algorithm for redundant robots is presented in this paper. This algorithm incorporates the neural networks and pseudodistance function D
p in the framework of resolved motion rate control. Thus, it is well suited for real-time implementation. Robot arm kinematic control is carried out by the Hopfield network. The connection weights of the network can be determined from the current value of Jacobian matrix at each sampling time, and joint velocity commands can be generated from the outputs of the network. The obstacle avoidance task is achieved by formulating the performance criterion as D
p>d
min (d
min represents the minimal distance between the redundant robot and obstacles). Its calculation is only related to some vertices which are used to model the robot and obstacles, and the computational times are nearly linear in the total number of vertices. Several simulation cases for a four-link planar manipulator are given to prove that the proposed collision-free trajectory planning scheme is efficient and practical. 相似文献
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This article presents a fast self-localization method based on ZigBee wireless sensor network and laser sensor, an obstacle
avoidance algorithm based on ultrasonic sensors for a mobile robot. The positioning system and positioning theory of ZigBee
which can obtain a rough global localization of the mobile robot are introduced. To realize accurate local positioning, a
laser sensor is used to extract the features from environment, then the environmental features and global reference map can
be matched. From the matched environmental features, the position and orientation of the mobile robot can be obtained. To
enable the mobile robot to avoid obstacle in real-time, a heuristic fuzzy neural network is developed by using heuristic fuzzy
rules and the Kohonen clustering network. The experiment results show the effectiveness of the proposed method. 相似文献
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雷道仲 《网络安全技术与应用》2014,(7):88-89
红外传感器在家用电器遥控和机器人避障方面有着广泛的应用,笔者根据红外传感器的这一特性设计出一款教育机器人避障电路,介绍了红外传感器在机器人避障电路中的应用,给出红外传感器与单片机系统的硬件接口电路和避障软件的编程思路,并通过测试,得出了影响红外传感器避障的相关因素,并提出了改进的方法和措施. 相似文献
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智能移动机器人的超声避障研究 总被引:1,自引:0,他引:1
智能移动机器人是机器人研究领域的重要方向,是当前机器人领域中最活跃的研究主题之一.在分析了智能移动机器人避障常用传感器的基础上,提出了基于多超声传感器的移动机器人的超声避障系统.介绍了超声避障系统的模糊控制规则和非模糊化,并给出了实验结果.实验结果表明,模糊控制机理和策略易于接受和理解,便于应用开发,模糊避障算法对环境有很大的适应性,机器人在不同的环境条件下实现了避障. 相似文献
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针对移动机器人局部动态避障路径规划问题开展优化研究。基于动态障碍物当前历史位置轨迹,提出动态障碍物运动趋势预测算法。在移动机器人的动态避障路径规划过程中,考虑障碍物当前的位置,评估动态障碍物的移动轨迹;提出改进的D*Lite路径规划算法,大幅提升机器人动态避障算法的效率与安全性。搭建仿真验证环境,给出典型的单动态障碍物、多动态障碍物场景,对比验证了避障路径规划算法的有效性。 相似文献
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改进蚁群算法及其在机器人避障中的应用 总被引:1,自引:0,他引:1
提出了一种改进蚁群算法.首先针对蚁群算法在构造解过程中收敛速度慢且容易陷入局部最优,提出了在蚁群搜索路径过程中,通过建立α(信息素启发式因子)和β(期望启发式因子)的互锁关系,动态自适应调整α、β;其次针对蚁群算法在面对凹形障碍物易陷入死锁,降低搜索效率,提出了广义信息素更新规则;最后利用栅格法进行静态已知环境建模,通过不同规模TSP的仿真验证了该方法的可行性和有效性,同时将其应用到机器人避障并取得了较好实验效果。 相似文献
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为了更好地解决移动机器人在未知环境下的自主避障问题,采用多传感器信息融合的方法,通过多个超声传感器对障碍物信息进行采集。合理确立模糊控制器的输入输出,通过模糊推理将障碍物距离信息模糊化,建立模糊规则并解模糊,以达到对移动机器人的安全避障的控制。通过建立移动机器人运动模型,设计了仿真平台,得到实验结果表明:该算法具有良好的可行性。 相似文献
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分析了井下钻孔机器人避障中超声波传感器的局限性,并提出解决的方案。着重指出对超声波进行温度、湿度补偿,尝试用Elman反馈神经网络逼近函数。Elman网络隐含层采用"Tansig"激活函数,输出层用"Pureline"激活函数,保证了只要有足够多的隐含层神经元个数,网络就可以任意精度逼近任意函数。经实验验证:对超声测距进行温度、湿度补偿后,其测量精度提高了2个数量级。大大改善系统中避障模块的工作效率,提高了钻孔机器人躲避障碍物的能力。 相似文献
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多传感器信息融合在四足机器人避障中的应用 总被引:1,自引:0,他引:1
为提高仿生四足机器人在复杂、动态环境下对障碍物位置信息的感知能力,针对机器人在结构化路面上以Walk步态行走的情况,对双目视觉传感器和超声测距传感器获取的障碍物距离信息进行融合研究.首先,对两种传感器获取的障碍物距离信息进行卡尔曼滤波,降低环境中杂波的影响,然后,根据STF融合算法,利用滤波后得到的两组状态向量的估计值和协方差矩阵进行融合处理.仿真结果表明:滤波后的距离信息的估计值曲线很好地跟踪了真实值曲线,说明卡尔曼滤波算法发挥了良好的滤波作用;与融合前相比,融合后的距离信息估计值的方差明显减小,说明融合后的障碍物位置信息更加准确,满足了仿生四足机器人在复杂、动态环境下作业和行进的精度要求. 相似文献
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提出一种新的基于传感器信息的自治式水下机器人(AUV)动态避障方法。介绍了传感器的工作原理。通过栅格法把传感器采集的AUV运行环境障碍信息进行合理描述,并预测动态障碍物的速度,保证AUV能够根据传感器信息躲避障碍物,达到航行要求。最后,通过仿真实验对机器人自主避障能力进行了验证。 相似文献
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基于Cortex-M0微控制器设计超声波、红外和碰撞等多传感器硬件系统感知机器人工作环境,应用模糊神经网络对采集的数据进行信息融合处理,输出结果用来控制吸尘机器人的定位与避障。实验证明,多传感器硬件系统和基于模糊神经网络的避障算法大大提高了吸尘机器人的定位与避障精度,对不同的工作环境也具有良好的鲁棒性。 相似文献
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Traversability Analysis and Path Planning for a Planetary Rover 总被引:4,自引:0,他引:4
Donald B. Gennery 《Autonomous Robots》1999,6(2):131-146
A method of analyzing three-dimensional data such as might be produced by stereo vision or a laser range finder in order to plan a path for a vehicle such as a Mars rover is described. In order to produce robust results from data that is sparse and of varying accuracy, the method takes into account the accuracy of each data point, as represented by its covariance matrix. It computes estimates of smoothed and interpolated height, slope, and roughness at equally spaced horizontal intervals, as well as accuracy estimates of these quantities. From this data, a cost function is computed that takes into account both the distance traveled and the probability that each region is traversable. A parallel search algorithm that finds the path of minimum cost also is described. Examples using real data are presented. 相似文献
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This paper is concerned with the problem of reactive navigation for a mobile robot in an unknown clustered environment. We will define reactive navigation as a mapping between sensory data and commands. Building a reactive navigation system means providing such a mapping. It can come from a family of predefined functions (like potential fields methods) or it can be built using ‘universal’ approximators (like neural networks). In this paper, we will consider another ‘universal’ approximator: fuzzy logic. We will explain how to choose the rules using a behaviour decomposition approach. It is possible to build a controller working quite well but the classical problems are still there: oscillations and local minima. Finally, we will conclude that learning is necessary for a robust navigation system and fuzzy logic is an easy way to put some initial knowledge in the system to avoid learning from zero. 相似文献
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Jianan Wang 《International journal of control》2013,86(12):2606-2621
Multi-agent consensus problem in an obstacle-laden environment is addressed in this study. A novel optimal control approach is proposed for the multi-agent system to reach consensus as well as avoid obstacles with a reasonable control effort. An innovative nonquadratic penalty function is constructed to achieve obstacle avoidance capability from an inverse optimal control perspective. The asymptotic stability and optimality of the consensus algorithm are proven. In addition, the optimal control law only requires local information from the communication topology to guarantee the proposed behaviour, rather than all agents’ information. The consensus and obstacle avoidance are validated through various simulations. 相似文献