IR Sensors Array for Robots Localization Using K Means Clustering Algorithm
Israa AL-Forati, Abdulmuttalib Rashid, Alaa Al-Ibadi
- 发表年份
- 2019
- 引用次数
- 12
摘要
The position of multi-robot system in an indoor localization system is successfully estimated using a new algorithm. The localization problem is resolved by using an array of IR receiver sensors distributed uniformly in the environment. The necessary information about the localization development is collected by scanning the IR sensor array in the environment. The scheme of scanning process is done column by column to recognize and mention the position of IR receiver’s sensors, which received signals from the IR transmitter that is fixed on the robot. This principle of scanning helps to minimize the required time for robot localization. The k-means clustering algorithm is used to estimate the multi-robot locations by isolating the labeled IR receivers into clusters. Basically the multi-robot position is estimated to be the middle of each cluster. Simulation results demonstrate the advances algorithm in estimation the multi-robot positions for various dimensional IR receiver’s array.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002