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Robot Obstacle Avoidance and Navigation Control Algorithm Research Based on Multi-Sensor Information Fusion

机译:基于多传感器信息融合的机器人避障与导航控制算法研究

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Multi-sensor information fusion technology has very extensive application prospect in robot obstacle avoidance. To solve the problems of robot obstacle avoidance and path scheduling for mobile robots, this article proposes a T-S based FNN multi-sensor information fusion approach integrated with fuzzy logic and neural network. It analyzes the learning algorithm based on gradient in FNN and improved the computing process, which avoids possible oscillation and reduces training time of network. Then the secondary fusion scheme implemented on robot obstacle avoidance and navigation control is designed. The simulations verify that our approach is feasible and effective in obstacle avoidance and path planning for mobile robots.
机译:多传感器信息融合技术在机器人避障方面具有广阔的应用前景。为解决移动机器人的机器人避障和路径调度问题,提出了一种融合了模糊逻辑和神经网络的基于T-S的FNN多传感器信息融合方法。通过对FNN中基于梯度的学习算法进行分析,改进了计算过程,避免了可能的振荡,减少了网络的训练时间。然后设计了在机器人避障和导航控制上实现的二次融合方案。仿真验证了我们的方法在移动机器人避障和路径规划中是可行和有效的。

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