Simulation of Rapidly-Exploring Random Trees in Membrane Computing with P-Lingua and Automatic Programming

Methods based on Rapidly-exploring Random Trees (RRTs) have been widely used in robotics to solve motion planning problems. On the other hand, in the membrane computing framework, models based on Enzymatic Numerical P systems (ENPS) have been applied to robot controllers, but today there is a lack of planning algorithms based on membrane computing for robotics. With this motivation, we provide a variant of ENPS called Random Enzymatic Numerical P systems with Proteins and Shared Memory (RENPSM) addressed to implement RRT algorithms and we illustrate it by simulating the bidirectional RRT algorithm. This paper is an extension of [21]a. The software presented in [21] was an ad-hoc simulator, i.e, a tool for simulating computations of one and only one model that has been hard-coded. The main contribution of this paper with respect to [21] is the introduction of a novel solution for membrane computing simulators based on automatic programming. First, we have extended the P-Lingua syntax –a language to define membrane computing models– to write RENPSM models. Second, we have implemented a new parser based on Flex and Bison to read RENPSM models and produce source code in C language for multicore processors with OpenMP. Finally, additional experiments are presented.Ministerio de Economía, Industria y Competitividad TIN2017-89842-

Implementing Obstacle Avoidance and Follower Behaviors on Koala Robots Using Numerical P Systems

Membrane controllers have been developed using Numerical P Systems and their extension, Enzymatic Numerical P Systems, for controlling mobile robots like e- puck and Khepera III. In this paper we prove that membrane controllers can be easily adapted for other types of robotic platforms. Therefore, obstacle avoidance and follower behaviors were adapted for Koala robots. The membrane controllers for Koala robots have been tested on real and simulated platforms. Experimental results and performance analysis are presented

Generation of rapidly-exploring random trees by using a new class of membrane systems

Methods based on Rapidly-exploring Random Trees (RRTs) have been in use in robotics to solve motion planning problems for nearly two decades. On the other hand, models based on Enzymatic Numerical P systems (ENPS) have been applied to robot controllers for more than six years. These controllers in real robots handle the power of motors ac- cording to motion commands usually generated by planning algorithms, but today there is a lack of planning algorithms based on membrane sys- tems for robotics. With this motivation, we provide in this paper a new variant of ENPS called Random Enzymatic Numerical P systems with Proteins and Shared Memory (RENPSM) oriented to RRTs for planning in robotics and we illustrate it by presenting a model for generation of RRTs with holonomic limitations. We are working on the ENPS frame- work with the idea of moving towards a complete mobile robot system based on membrane systems, i.e. including controllers and planning; and we have incorporated new ingredients into the ENPS framework to meet the requirements of the RRT generation algorithm

Simulating Large-Scale ENPS Models by Means of GPU

Enzymatic Numerical P Systems (ENPS), an extension of Numerical P Systems, have been successfully applied to model robot controllers. GPGPU is an innovative technological paradigm which applies the parallel architecture of graphic cards to solve parallel, general{purpose problems. In previous work, a GPU simulator for ENPS was introduced. In this paper, a performance analysis on the simulator is performed in order to experimentally measure the speed-up factors resulting from the simulations.Ministerio de Ciencia e Innovación TIN2009-13192Junta de Andalucía P08-TIC-0420

Improving the Universality Results of Enzymatic Numerical P Systems

This paper provides the proof that Enzymatic Numerical P Sytems with deterministic, but parallel, execution model are universal, even when the production functions used are polynomials of degree 1. This extends previous known results and provides the optimal case in terms of polynomial degree

The Pole Balancing Problem with Enzymatic Numerical P Systems

Pole balancing is a control benchmark widely used in engineering. It involves a pole a xed to a cart via a joint which allows movement along a single axis. In this problem, the movement of the cart is restricted to the horizontal axis by a track and the pole is free to move about the horizontal axis of the pivot. The system is extremely unstable and, the cart must be in constant movement in order to preserve the equilibrium and avoid the fall of the pendulum. In this paper, we study the pole balancing problem in the framework of Enzymatic Numerical P Systems and provide some clues for using them in more complex systems.Ministerio de Economía y Competitividad TIN2012-3743

Open Problems, Research Topics, Recent Results on Numerical and Spiking Neural P Systems (The "Curtea de Arge s 2015 Series")

A series of open problems and research topics are formulated, about numer- ical and spiking neural P systems, initially prepared as a working material for a three months research stage of the second and the third co-author in Curtea de Arge s, Roma- nia, in the fall of 2015. Further problems were added during this period, while certain problems were addressed in this time; some details and references are provided for such cases

Simulation of Rapidly-Exploring Random Trees in Membrane Computing with P-Lingua and Automatic Programming

Methods based on Rapidly-exploring Random Trees (RRTs) have been widely used in robotics to solve motion planning problems. On the other hand, in the membrane computing framework, models based on Enzymatic Numerical P systems (ENPS) have been applied to robot controllers, but today there is a lack of planning algorithms based on membrane computing for robotics. With this motivation, we provide a variant of ENPS called Random Enzymatic Numerical P systems with Proteins and Shared Memory (RENPSM) addressed to implement RRT algorithms and we illustrate it by simulating the bidirectional RRT algorithm. This paper is an extension of [21]a. The software presented in [21] was an ad-hoc simulator, i.e, a tool for simulating computations of one and only one model that has been hard-coded. The main contribution of this paper with respect to [21] is the introduction of a novel solution for membrane computing simulators based on automatic programming. First, we have extended the P-Lingua syntax –a language to define membrane computing models– to write RENPSM models. Second, we have implemented a new parser based on Flex and Bison to read RENPSM models and produce source code in C language for multicore processors with OpenMP. Finally, additional experiments are presented

Membrane Computing and Economics: A General View

Three are the points we briefly discuss here: using membrane computing tools for efficient computing/optimization, the possibilities of using “general" membrane computing (P systems using multisets of symbol objects processed by biochemical-like evolution rules) as a framework for modeling economic processes, and the numerical P systems, a class of computing devices explicitly defined with a motivation related to economics. The discussion is rather informal, only pointing out research directions and providing bibliographical information