A Generic Guide for Using Membrane Computing in Robot Control

As various theoretical and practical details of using membrane computing models have been presented throughout the book, certain details might be hard to find at a later time. For this reason, this chapter provides the reader with a set of checkmark topics that a developer should address in order to implement a robot controller using a membrane computing model. The topics discussed address areas such as: (1) robot complexity, (2) number of robots, (3) task complexity, (4) simulation versus real world execution, (5) sequential versus parallel implementations. This chapter concludes with an overview of future research directions. These directions offer possible solutions for several important concerns: the development of complex generic algorithms that use a high level of abstraction, the design of swarm algorithms using a top-down (swarm-level) approach and ensuring the predictability of a controller by using concepts such as those used in real-time operating systems.

Membrane Computing

The theoretical computing models that are used throughout this book are described in this chapter. These models are based on the initial P system model and include: Numerical P systems, Enzymatic Numerical P systems, P colonies and P swarms. Detailed examples and execution diagrams help the reader allow the reader to understand the functioning principle of each model and also its potential in various applications. The similarity between P systems (and their variants) and robot control models is also addressed. This analysis is presented to the reader in a side-by-side manner using a table where each row represents an analysis topic. Among others we mention: (1) Architectural structure, (2) Modularity and hierarchy, (3) Input-output relationships, (4) Parallelism.

P Colonies for the Control of Single and Multiple Robots

The fourth chapter is dedicated to the topic of controlling single and multiple robots using P colonies. The open-source P colony simulator Lulu is used as a software basis that allowed for the development of a discrete robot controller. The chapter is organized around a set of experiments that are ordered by difficulty and are described using the P colony model and execution diagrams. These diagrams allow the reader to view when and what will be the response of the robot to a given input signal. Several screenshots are also presented to aid in understanding this process. All of the experiments can be fully replicated by using the input files provided within the chapter or the on-line guidelines that are available at http://membranecomputing.net/IGIBook.

An Overview of Swarm Robotics

Robotic swarms represent the application target of the studies presented in this book and therefore required the reader to be acquainted with the main concepts behind this branch of robotics. The introduction of swarm robotics principles is done only after presenting multi-robot systems, in comparison with single robot systems. Among the concepts that are defined in this chapter we mention: swarm robotic system, stigmergy and neighborhoods. After this theoretical introduction, the chapter continues with a presentation of robotic platforms that can be used to validate swarm algorithms. Among the robots listed are the Kilobot, the e-puck and the Khepera. As swarm robotics generally requires a large number of individuals, the costs of running experiments on real robots can become high. For this reason, robot simulation platforms are also discussed at the end of this chapter.

Software for Membrane Computing

In order to use membrane computing models for real life applications there is a real need for software that can read a model from some form of input media and afterwards execute it according to the execution rules that are specified in the definition of the model. Another requirement of this software application is for it to be capable of interfacing the computing model with the real world. This chapter discusses how this problem was solved along the years by various researchers around the world. After presenting notable examples from the literature, the discussion continues with a detailed presentation of three membrane computing simulators that have been developed by the authors at the Laboratory of Natural Computing and Robotics at the Politehnica University of Bucharest, Romania.