本文提出了一种基于神经网络改进算法的机器人逆运动学的求解方法。
A new method of solving inverse kinematics of robots based on improvement of neural networks is presented in this paper.
为了实现定位抓取任务，提出基于网络的直角坐标机器人视觉控制系统。
Network based visual servo system of the orthogonal coordinate robot was proposed, in order to implement grasping job.
介绍了基于生物激励神经网络的移动机器人路径规划。
The biologically inspired neural networks based path planning approaches of mobile robot were introduced.
基于CAN总线实现了地面爬行机器人的通信网络。
The communication network of Ground Creeping Robot is established based on CAN bus.
基于Q强化学习与CMAC神经网络的移动机器人局部路径规划研究。
Research on local path planning of mobile robot based on Q reinforcement learning and CMAC neural networks.
本文从一般动力学标定和基于神经网络的动力学标定两方面对现有机器人动力学标定方法和研究现状进行了分析和总结。
An overview of the robot dynamic calibration methods and research status was presented from two aspects: general dynamic calibration and dynamic calibration based on neural networks.
提出一种新的基于神经网络的机器人模型参考自适应控制方法。
A new robot model reference adaptive control method based on neural networks is presented.
本文提出一种基于T -S模型的变结构模糊神经网络直接逆模型控制器，并将其应用于移动机器人的运动控制中。
A direct inverse model controller of fuzzy neural network with changeable structure based on t s inference is presented in this paper and it is used to the motion control of mobile robot.
本文就机器人网络遥操作系统及基于事件的控制方法进行了研究。
This thesis presents the researches of on teleoperation of Internet based robots and event based control scheme.
基于网络的遥操作机器人系统，本质上是一个分布式计算系统，所以相应的软件必然是分布式应用软件。
A teleoperator system based on network is a distributed computing system if we look it from the computing mode point of view, so the software should be contributed application software.
为了满足室外移动机器人高速安全行驶的要求，提出了一种基于分段直线模型和增强型状态转移网络(atn)的车道识别方法。
A high speed lane detection method that satisfies the safety requirements of outdoor mobile robots was developed based on the segment-line road model and augmented transition networks (ATN).
在分析传统机器人位姿标定方法的基础上，提出了一种新的机器人标定方法：基于神经网络的逆标定方法。
An innovative robot calibration approach: inverse robot calibration based on neural network, is proposed in this paper, based on the analysis of traditional calibration approach.
为解决机构复杂的拟人机器人运动学和动力学问题，提出了基于传统机理结合神经网络的建模方法。
To resolve the kinematics modeling and dynamics modeling of a humanoid robot with complicated machine, a modeling method based on the conventional mechanism combined with neural network is presented.
给出了基于自构型快速BP网络的并联机器人位置正解通用方法并以雕刻机器人为例进行了分析。
A general forward displacement solution for parallel robot based on self-configuration quick BP neural network is presented, and analysis result for the engraving robot is given.
提出一种基于步态规划分级结构的自适应网络模糊推理系统控制策略，该方法不需要确定双足机器人运动学和动力学模型。
Proposed an adaptive network fuzzy inference system control strategy based on hierarchy structure of gait planning, which do not require detailed kinematics or dynamic biped models.
本文的主要内容是在基于有线和无线相融合的混合网络中，针对移动机器人多传感器采集数据的性能要求，研究如何提高移动机器人远程通信的质量。
The main content for this paper is to make a research on how to enhance the quality of the remote communication in view of the performance requirement of the robot's multi-sensors data.
根据机器人视觉识别系统所要完成的具体识别任务，构建一个基于神经网络的视觉识别系统。
According to the specific identification task that robot vision recognition system will accomplish, the thesis builds a neural network based visual recognition system.
充分考虑到智能割草机器人的工程实用性，基于RBF神经网络算法，提出在无人为标识的草坪区域中建立边界和识别边界的新方案。
With the full consideration of engineering practicability, based on the RBF neural network, a new solution to the boundary set-up and identification of unmarked operational area is proposed.
针对双足机器人控制问题，提出了一种基于模糊神经网络的混杂控制方法。
The paper presents a fuzzy neural networks hybrid control of biped robot control problem.
本文以轮式移动机器人为平台，主要研究基于无线传感器网络的移动机器人路径跟踪问题。
With the platform of wheeled mobile robot, this paper mainly studies the path tracking problem based on the Wireless Sensor Networks.
其次改进了一种基于神经网络的三维机器人路径规划环境原型系统，为混合路径规划算法的提出准备了较精确的适应度函数。
Next, improves one three dimensional robot path planning environment prototype system kind based on the neural network, prepares the precise sufficiency function for the mixed algorithm.
提出了一种基于移动设备的网络自主机器人系统的体系结构，设计并实现了系统的安全机制以及人-机器人交互方式。
The architecture of Internet robot with mobile devices is presented and the security mechanisms and human-robot interaction way is designed.
这是通过使用一对卷积神经网络(CNN)基于识别模块中的机器人从视频如何学习完成。
This is done by using a pair of Convolutional Neural Network (CNN) based recognition modules.
因此，同时考虑机器人运动学和动力学模型，提出基于神经网络的轨迹跟踪算法，仿真结果表明算法具有较强的鲁棒性。
So, we design a trajectory tracking algorithm based on NNs, considering both kinematic and dynamical model, and the simulation results demonstrate that this algorithm has good robustness.
将粗集合理论与神经网络相结合，提出一种基于粗神经网络的新的信息融合方法，用于仿人智能机器人的语音融合。
Integrating rough set theory with neural network theory, a novel information fusion method based on rough neural network is proposed. It is used in speech fusion of humanoid intelligent robots.
以轮式移动机器人驱动系统为主要研究对象，提出一种基于神经网络的分析与试验相结合的建模方法。
This paper studies mainly a wheeled mobile robot drive system with modeling method proposed based on combination of neural network analysis and experiment.
针对数学模型复杂的轮式机器人的转向控制问题，使用基于遗传算法的模糊神经网络转向控制方法。
As the mathematic model of the wheeled mobile robot is very complicated, a GA (genetic algorithms) fuzzy neural network method is presented for its steering control.
针对数学模型复杂的轮式机器人的转向控制问题，使用基于遗传算法的模糊神经网络转向控制方法。
As the mathematic model of the wheeled mobile robot is very complicated, a GA (genetic algorithms) fuzzy neural network method is presented for its steering control.
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