基于可靠性函数的多移动机器人全覆盖路径规划算法

Shuai Zhang, Jianlei Zhang
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引用次数: 0

摘要

未知区域的多机器人完全覆盖问题是指多机器人在未知环境中通过传感器获取环境信息,并相互协作搜索特定的任务区域。针对多移动机器人的全覆盖路径规划问题,提出了一种基于网格可靠性函数的路径规划算法。首先,根据环境、障碍物、覆盖网格和未覆盖网格信息计算位置可靠性函数值;其次,为了降低路径重复率,提高覆盖效率,引入方向可靠性函数来调整网格函数值,有效地引导机器人到未覆盖的网格;第三,在机器人覆盖区域时,确保机器人之间不会过度靠近,机器人之间的密度由密集可靠度函数值衡量。最后,通过与仿生神经网络算法在盒子仿真和露台世界模拟真实环境两种场景下的对比,验证了本文算法具有较低的重复率和较短的轨迹长度。
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Complete-Coverage Path Planning Algorithm of Multiple Mobile Robots Based on Reliability Functions
The multi-robot complete coverage problem in unknown area refers to that multi-robots obtain environment information through their sensors in unknown environment, and cooperate with each other to search the specific task area. For the complete-coverage path planning of multiple mobile robots, an algorithm based on grid reliability function was proposed. Firstly, positional reliability function value is calculated according to the information of the environment, the obstacles, covered grids and uncovered grids; Secondly, in order to reduce the path repetition rate and improve the coverage efficiency, the directional reliability function is introduced to adjust the grid function values and guides robots to uncovered grid efficiently; Thirdly, the robots make sure that there will be no excessive proximity between robots while robots cover the area, the density between robots is measured by dense reliability function value. In the final session, by compared with bio-inspired neural network algorithm in two scenarios: box simulation and simulated real environment in gazebo world, the algorithm proposed in this paper was verified to own lower repetition rate and shorter trajectory length.
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