Description: 果蔬收获机器人是机器人技术在农业中的具体应用，基于避障的路径规划是果蔬收获机器人主要
的研究内容。由于农业机器人作业环境的复杂性和非结构性，神经网络籽是其重要的研究方法。为此，介
绍了神经网络的特点，重点分析了采用神经网络描述果蔬收获机器人工作环境的基本思路，最后给出了黄
瓜采摘机器人的具体分析实例，对农业机器人工作环境的描述具有较高的参考价值。-Fruit and vegetable harvesting robot is the robot technology in agriculture specific application, based on the obstacle avoidance path planning is the main fruit and vegetable harvesting robot research. Operating environment as a result of agricultural robot complexity and non-structural, neural network is an important seed of research methods. To this end, introduce the characteristics of neural networks, focusing on the use of neural network analysis of fruit and vegetable harvesting robot description of the working environment of the basic ideas, the final cucumber picking robot is given specific examples of analysis of agricultural robot description of the work environment has a high reference value. Platform: |
Size: 182272 |
Author:高子 |
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Description: 动态环境下基于势场原理的避障方法
提出了一种新颖的控制方案，即采用神经网络预测控制器来控制机器人的力／位置．这种控
制器能任意逼近机器人这种不确定对象，不用知道系统的精确结构，同时由于预测控制的加入，使系
统在线计算方便，控制质量提高了-Dynamic environment based on the principle of potential field obstacle avoidance method
A novel control scheme, namely, the use of neural network predictive controller to control the robot s force/position. This control
System of robots capable of approaching any object to such uncertainty, do not know the precise structure of the system, at the same time as a result of the addition of predictive control, so that the Department of
Convenience of online computing integration, improved quality control Platform: |
Size: 66560 |
Author:janet |
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Description: 摘 要：果蔬收获机器人是机器人技术在农业中的具体应用，基于避障的路径规划是果蔬收获机器人主要
的研究内容。由于农业机器人作业环境的复杂性和非结构性，神经网络籽是其重要的研究方法。为此，介
绍了神经网络的特点 ，重点分析了采用神经网络描述果蔬收获机器人工作环境的基本思路 ，最后给出了黄瓜采摘机器人的具体分析实例，对农业机器人工作环境的描述具有较高的参考价值。 -Abstract: The fruit and vegetable harvesting robot is the robot technology in agriculture specific application, based on the obstacle avoidance path planning is the main fruit and vegetable harvesting robot research. Operating environment as a result of agricultural robot complexity and non-structural, neural network is an important seed of research methods. To this end, introduced the characteristics of neural networks, focusing on the use of neural network analysis of fruit and vegetable harvesting robot describes the basic idea of the working environment, and finally given a cucumber harvesting robot specific examples of analysis of agricultural robot description of the work environment has a high reference value. Platform: |
Size: 182272 |
Author:彭彭 |
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Description: 传感器信息融合及其在机器人中的应用
摘要：多传感器信息融合即融合多个传感器提供的冗余、互补或更实时的信息，可以获得系统所需的
更准确和更精确的信息。介绍了神经网络融合方法，探讨了信息融合技术在机器人方面的应用。机器
人避障实验验证了所提方法的有效性。
关键词：多传感器信息融合(MIF)；神经网络；移动机器人；避障；-Sensor Information Fusion and Its Application in Robot Summary: Multi-sensor data fusion or integration of multiple sensors to provide redundant, complementary or even real-time information systems required to obtain a more accurate and more precise information. Describes the neural network fusion method to explore the information fusion technology in robotics applications. Robot obstacle avoidance experimental verification of the proposed method. Key words: multi-sensor data fusion (MIF) neural network mobile robot obstacle avoidance Platform: |
Size: 232448 |
Author:loevppp |
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Description: 这是一篇介绍BP神经网络在移动机器人路径规划方面的论文-Abstract：Improves the BP neural network algorithm，so the shortage of path —planning with the
．
BP neural
network algorithm is overcomed ．The simulation results indicate that on the bases of accessional momentum
method can eficiently improve this algorithm in convergence speed．At last，mobile robot dynamic path plan—
ning simulation is carried out in the environment with immobile and mobile obstacle．the simulation result indi—
cates that the method is feasible. Platform: |
Size: 198656 |
Author:王风 |
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Description: ：针对移动机器人传统路径规划算法效率不高，寻优能力差等问题，提出一种基
于神经网络和粒子群优化算法相结合的移动机器人路径规划方法．该方法利用神经网
络实现大量的并行和分布计算，发挥PSO简单、容易实现的优点，提高了路径规划的计
算效率和可靠性．仿真结果表明，这种新路径规划方法是可行且有效的．-The quality and eficiency of calculation is the two puzzling problems in the tradi—
tional algorithm for the robot path planning．In this paper，a new method of obstacle avoidance
and path planning based on neural network and particle swarm optimization is proposed．In
this method，a neural network is used to realize substantive parallel and distributed compu—
ting．And also this exerts the merit of PSO，which improves the computational eficiency and
reliability．As it is proved by analysis and test，that a better result is obtained by the pro—
posed algorithm． Platform: |
Size: 162816 |
Author:王风 |
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Description: ：为提高移动机器人在未知环境下避障行为的成功率，通过对障碍物信息的输人，从控制输出数据中找出避
障行为模式，生成相应的模糊逻辑控制规则，并把模糊控制算法引入到神经网络中，使得模糊控制器规则的在线精
度和神经网络的学习速度均有较大的提高，使移动机器人具有较为迅速的反应能力，实现机器人连续、快速地避障
并最终到达目标．系统仿真证明了模糊神经网络在移动机器人路径选择中的智能性．-To enable the mobile robot in unknown environment obstacle—avoiding behavior of
Success，based on the information input of obstacles and from the control of output data to find a
obstacle—avoiding behavior model，and To create the fuzzy logic rules，a fuzzy control algorithm is
introduced to the neural network，allowing mobile robot more rapid response ability and to
achieve a robot， and finally reach the target of obstacle avoidance． system sim ulation proves a
fuzzy neural network in mobile robot path choice of intelligence． Platform: |
Size: 290816 |
Author:王风 |
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Description: 基于模糊神经网络的多传感器信息融合，提出了一种简单、有效的分区算法来确定障碍物的距离和方位。采用BP神经网络对障碍物环境进行分类以及模式识别，为移动机器人的导航和避障提供了一种有效的方法。-Fuzzy neural network based multi-sensor information fusion, we propose a simple and effective algorithm to determine the partition barrier distance and direction. BP neural network to classify the environment of the obstacles and pattern recognition for mobile robot navigation and obstacle avoidance provides an effective method. Platform: |
Size: 261120 |
Author:wang |
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Description: 神经网络机器人避障matlan仿真程序可模拟机器器人在空间的避障动作 ，经测试可直接使用。
-The neural network robot obstacle avoidance matlan simulation program can simulate the machine control space to avoid this obstacle has been tested and can be used directly. Platform: |
Size: 1024 |
Author:bl |
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Description: 我们用三个方向的距离，把它们放进简单的神经网络输出至Jackal机器人。让它尝试不同的轨迹和方向，然后找到完美的路线，利用迭代学习与遗传 算法，从而达到完美的避障。该项目有着广泛的应用，如自动驾驶，如扫地机器人我们也可以看到Jackal变得越来越智能化连续学习，这是非常有趣的。(We use the distance from three directions and put them into the simple neural
network to output to the Jackal robot. By letting Jackal try different trajectories
and directions, and then find the perfect route, iterative learning with genetic
algorithm, so as to achieve the perfect obstacle avoidance.This project can have
a wide range of applications, such as auto driving, such as sweeping robots,
and we can also see Jackal becoming more and more intelligent in continuous
learning, which is very interesting.) Platform: |
Size: 228352 |
Author:蛋挞Z |
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Search - robot obstacle neural network