Affiliations: [a] School of Information Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, China | [b] School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China | [c] College of Information Science and Technology, Chengdu University of Technology, Chengdu, Sichuan, China | [d] COL Laboratory, School of Computer Science, University of Nottingham, Nottingham, UK | [e] College of Control Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, China
Correspondence:
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Corresponding author: Xiantai Gou, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, Sichuan, China. E-mail: [email protected]; Ferrante Neri, School of Computer Science, Jubilee Campus, Wollaton Road, Nottingham NG8 1BB, UK. E-mail: [email protected].
Abstract: Membrane computing models are parallel and distributed natural computing models. These models are often referred to as P systems. This paper proposes a novel multi-behaviors co-ordination controller model using enzymatic numerical P systems for autonomous mobile robots navigation in unknown environments. An environment classifier is constructed to identify different environment patterns in the maze-like environment and the multi-behavior co-ordination controller is constructed to coordinate the behaviors of the robots in different environments. Eleven sensory prototypes of local environments are presented to design the environment classifier, which needs to memorize only rough information, for solving the problems of poor obstacle clearance and sensor noise. A switching control strategy and multi-behaviors coordinator are developed without detailed environmental knowledge and heavy computation burden, for avoiding the local minimum traps or oscillation problems and adapt to the unknown environments. Also, a serial behaviors control law is constructed on the basis of Lyapunov stability theory aiming at the specialized environment, for realizing stable navigation and avoiding actuator saturation. Moreover, both environment classifier and multi-behavior coordination controller are amenable to the addition of new environment models or new behaviors due to the modularity of the hierarchical architecture of P systems. The simulation of wheeled mobile robots shows the effectiveness of this approach.
Keywords: Membrane computing, reactive navigation, autonomous mobile robot, behaviors coordination
