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Planning robot formations with fast marching square including uncertainty conditions

机译:规划具有快速进场的机器人编队,包括不确定性条件

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摘要

This paper presents a novel algorithm to solve the robot formation path planning problem working under uncertainty conditions such as errors the in robot's positions, errors when sensing obstacles or walls, etc. The proposed approach provides a solution based on a leader-followers architecture (real or virtual leaders) with a prescribed formation geometry that adapts dynamically to the environment. The algorithm described herein is able to provide safe, collision-free paths, avoiding obstacles and deforming the geometry of the formation when required by environmental conditions (e.g. narrow passages). To obtain a better approach to the problem of robot formation path planning the algorithm proposed includes uncertainties in obstacles' and robots' positions. The algorithm applies the Fast Marching Square (FM~2) method to the path planning of mobile robot formations, which has been proved to work quickly and efficiently. The FM~2 method is a path planning method with no local minima that provides smooth and safe trajectories to the robots creating a time function based on the properties of the propagation of the electromagnetic waves and depending on the environment conditions. This method allows to easily include the uncertainty reducing the computational cost significantly. The results presented here show that the proposed algorithm allows the formation to react to both static and dynamic obstacles with an easily changeable behavior.
机译:本文提出了一种新颖的算法来解决在不确定条件下工作的机器人编队路径规划问题,例如机器人位置错误,感测障碍物或墙壁时的错误等。所提出的方法提供了一种基于领导者跟随架构的解决方案(真实或虚拟指挥仪)具有可动态适应环境的规定编队几何形状。本文所述的算法能够提供安全的,无碰撞的路径,当环境条件(例如狭窄的通道)要求时,避免障碍物并使地层的几何形状变形。为了获得更好的解决机器人编队路径规划问题的方法,提出的算法包括障碍物和机器人位置的不确定性。该算法将快速行进平方(FM〜2)方法应用于移动机器人编队的路径规划,已被证明可以快速有效地工作。 FM〜2方法是一种路径规划方法,没有局部最小值,可以为机器人提供平滑和安全的轨迹,从而根据电磁波的传播特性并根据环境条件创建时间函数。这种方法可以轻松地包含不确定性,从而显着降低计算成本。此处显示的结果表明,所提出的算法允许地层以容易改变的行为对静态和动态障碍物做出反应。

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