A real-time cooperative sweeping strategy for multiple cleaning robots

被引：50

作者：

Luo, CM ^{[1
]}

Yang, SX ^{[1
]}

机构：

[1] Univ Guelph, ARIS Lab, Sch Engn, Guelph, ON N1G 2W1, Canada

来源：

PROCEEDINGS OF THE 2002 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL | 2002年

关键词：

D O I：

10.1109/ISIC.2002.1157841

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a cooperative sweeping strategy of complete coverage path planning for multiple cleaning robots in a time-varying and unstructured environment is proposed using biologically inspired neural networks. Cleaning tasks require a special kind of trajectory being able to cover every unoccupied area in specified cleaning environments, which is an essential issue for cleaning robots and many other robotic applications. Multiple robots can improve the work capacity, share the cleaning tasks, and reduce the time to complete sweeping tasks. In the proposed model, the dynamics of each neuron in the topologically organized neural network is characterized by a shunting neural equation. Each cleaning robot treats the other robots as moving obstacles. Multiple cleaning robots can cooperate to achieve a common sweeping goal effectively. The robot path is autonomously generated from the dynamic activity landscape of the neural network, the previous robot location and the other robot locations. The proposed model algorithm is computationally efficient. The feasibility is validated by simulation studies on three cases of two cooperating cleaning robots.

引用

页码：660 / 665

页数：6

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