Wang, T., Ramik, D.M., Sabourin, C. and Madani, K. (2011) Machine-Learning for Heterogeneous Multi-Robots Systems in Logistic Application Frame. Proceedings of the 14th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR2011), Paris, September 2011, 207-222. http://dx.doi.org/10.1142/9789814374286_0024

has been cited by the following article:

• TITLE: A Control Strategy for Multi-Robot System Navigating in a Dynamic Environment

  AUTHORS: Ting Wang, Ryad Chellali, Yang Yi, Wen Qin, Mingzhu Wei

  KEYWORDS: A Control Strategy for Multi-Robot System Navigating in a Dynamic Environment

  JOURNAL NAME: Journal of Computer and Communications, Vol.3 No.11, November 19, 2015

  ABSTRACT: This paper introduces a new control strategy for heterogeneous multi-robots systems dedicated to industrial logistic setups. This control strategy is based on both distributed intelligence and machine learning and involves three parts: the rigid formation controller, the perception system and the path planner. Our controller is event-based and thus its control-coordination strategy can be self-adaptive and applied to real dynamic environment. During the navigating process, the multi-robots system derives the environment model, performs the path planning process that guaranties both the transportation constraints and the obstacle avoidance. For the validation, both simulation and real robot experiments are performed. The results show that the developed control strategy can be well used for realistic logistics applications.