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To avoid unmoving and moving obstacles using MKBC algorithm Path planning

机译：使用MKBC算法避免移动障碍物

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The problem of path planning for the autonomous vehicle in environment with moving and stationary obstacles is considered. An algorithm based on modified Kohonen rule and behavioural cloning (MKBC) is developed. The MKBC algorithm, as improvement of RBF neural network, uses the training values as weighting values, rather then values from the previous time instance. This enables an intelligent system to learn from examples (operator's demonstrations) to control a robot vehicle, in this case, to avoid stationary or moving obstacle. Important characteristic of the MKBC algorithm is polynomial complexity, while most other path planning algorithms are exponential. Experiments determined that it is robust to parameter change and suitable for real time application.

机译：考虑具有移动和静止障碍物的环境中的自动驾驶车辆的路径规划问题。提出了一种基于改进的Kohonen规则和行为克隆（MKBC）的算法。作为RBF神经网络的改进，MKBC算法使用训练值作为加权值，而不是先前时间实例的值。这使得智能系统可以从示例（操作员的演示）中学习，以控制机器人车辆，从而避免静止或移动的障碍物。 MKBC算法的重要特征是多项式复杂度，而其他大多数路径规划算法都是指数级的。实验确定，它对参数更改具有鲁棒性，适合实时应用。

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《Mechatronics, 2009. ICM 2009》|2009年|1-6|共6页
会议地点 Malaga(ES);Malaga(ES)
作者
Kulic R.; Vukic Z.;
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作者单位

Fac. of Comput. Sci., Megatrend Univ. in Belgrade, Belgrade;

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关键词
collision avoidance; computational complexity; mobile robots; neurocontrollers; radial basis function networks; MKBC algorithm; RBF neural network; autonomous vehicle; behavioural cloning; intelligent system; modified Kohonen rule; moving obstacles; path planning; polynomial complexity; robot vehicle; stationary obstacles; Behavioural clonning; Kohonen rule; neural network; robot vehicle path planning;

机译：避免碰撞;计算复杂度;移动机器人;神经控制器;径向基函数网络; MKBC算法; RBF神经网络;自动驾驶;行为克隆;智能系统;修改的Kohonen规则;移动障碍;路径规划;多项式复杂度;机器人车辆;平稳障碍行为克隆Kohonen规则神经网络机器人路径规划;

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专利

1. Methodology of Concept Control Synthesis to Avoid Unmoving and Moving Obstacles (II) [J] . Ranka Kulic, Zoran Vukic Journal of Intelligent & Robotic Systems: Theory & Application . 2006,第3期

机译：避免活动和移动障碍的概念控制综合方法论（II）
2. Methodology of concept control synthesis to avoid unmoving and moving obstacles [J] . Ranka Kulic, Zoran Vukic Journal of Intelligent & Robotic Systems: Theory & Application . 2003,第1期

机译：概念控制综合避免移动障碍物的方法
3. 3D path planning for underwater vehicles using five evolutionary optimization algorithms avoiding static and energetic obstacles [J] . Mohammad Pourmahmood Aghababa Applied Ocean Research . 2012,第Null期

机译：使用五种进化优化算法避免水下和静态障碍的水下车辆3D路径规划
4. To avoid Unmoving and Moving Obstacles Using MKBC algorithm: Path planning [C] . Ranka Kulic, Zoran Vukic IEEE International Conference on Mechatronics . 2009

机译：避免使用MKBC算法否则不动和移动障碍：路径规划
5. A biomimetic, energy-harvesting, obstacle-avoiding, path-planning algorithm for UAVs. [D] . Gudmundsson, Snorri. 2016

机译：一种用于无人机的仿生，能量收集，避障路径规划算法。
6. A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm [O] . Kun Wei, Bingyin Ren 2018

机译：基于改进RRT算法的机器人操纵器自主避障动态路径规划方法
7. OperativeCriticalPointBug algorithm-local path planning of mobile robot avoiding obstacles [O] . Subir Kumar Das, Ajoy Kumar Dutta, Subir Kumar Debnath 2020

机译：OperativeCricitPointBug算法 - 移动机器人的局部路径规划避免障碍物

To avoid unmoving and moving obstacles using MKBC algorithm Path planning

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