Catalin Buiu

Development of membrane controllers for mobile robots

The main contribution of this paper is the introduction of the new concept of membrane controller based on the structure and functioning of a deterministic numerical P system. The procedure for developing a membrane controller and for using it to control a mobile robot is explained and several test cases are given in which membrane controllers are used to control both simulated and real mobile robots and to generate various desired behaviours (obstacle avoidance, wall following, and follow the leader). The experiments reported in this paper validate the concept and prove that the performance of a membrane controller is comparable to or better than that of other controllers (such as fuzzy logic controllers).

Enzymatic numerical P systems - a new class of membrane computing systems

A P system represents a distributed and parallel computing model in which basic data structures are multi-sets, strings or numerical variables. Numerical P systems have been introduced for possible applications in economics. A simulator for numerical P systems (SNUPS) has been designed, implemented and made available to the scientific community by the authors of this paper. SNUPS allows the development of a wide range of applications, from modeling and simulation of ordinary differential equations, to design and simulation of computational blocks for cognitive architectures and of membrane controllers for autonomous mobile robots. This paper introduces a new class of membrane computing systems, that of enzymatic numerical P systems, in which enzyme-like variables allow the existence of more than one production function in each membrane. The way this new type of deterministic numerical P systems works and the corresponding implementation in SNUPS are detailed, together with an illustrative example.

Hybrid Educational Strategy for a Laboratory Course on Cognitive Robotics

This paper presents an innovative cognitive robotics laboratory course based on the latest developments in mobile robotics, communication networks, software agents, and educational technologies. The hybrid educational strategy combines simulation and experiments on real robots, as well as in-class experiments and remote control over the Internet, while the students are assisted by human tutors and artificial software agents. Evaluation data demonstrate the validity and attractiveness of this approach.

Chondroitin Sulfate Proteoglycans: Structure-Function Relationship with Implication in Neural Development and Brain Disorders

Chondroitin sulfate proteoglycans (CSPGs) are extracellular matrix components that contain two structural parts with distinct functions: a protein core and glycosaminoglycan (GAG) side chains. CSPGs are known to be involved in important cell processes like cell adhesion and growth, receptor binding, or cell migration. It is recognized that the presence of CSPGs is critical in neuronal growth mechanisms including axon guidance following injury of nervous system components such as spinal cord and brain. CSPGs are upregulated in the central nervous system after injury and participate in the inhibition of axon regeneration mainly through their GAG side chains. Recently, it was shown that some CSPGs members like aggrecan, versican, and neurocan were strongly involved in brain disorders like bipolar disorder (BD), schizophrenia, and ADHD. In this paper, we present the chemical structure-biological functions relationship of CSPGs, both in health state and in genetic disorders, addressing methods represented by genome-wide and crystallographic data as well as molecular modeling and quantitative structure-activity relationship.

A software tool for modeling and simulation of numerical P systems

UNLABELLED A P system represents a distributed and parallel bio-inspired computing model in which basic data structures are multi-sets or strings. Numerical P systems have been recently introduced and they use numerical variables and local programs (or evolution rules), usually in a deterministic way. They may find interesting applications in areas such as computational biology, process control or robotics. The first simulator of numerical P systems (SNUPS) has been designed, implemented and made available to the scientific community by the authors of this paper. SNUPS allows a wide range of applications, from modeling and simulation of ordinary differential equations, to the use of membrane systems as computational blocks of cognitive architectures, and as controllers for autonomous mobile robots. This paper describes the functioning of a numerical P system and presents an overview of SNUPS capabilities together with an illustrative example. AVAILABILITY SNUPS is freely available to researchers as a standalone application and may be downloaded from a dedicated website, http://snups.ics.pub.ro/, which includes an user manual and sample membrane structures.

Design and Evaluation of an Integrated Online Motion Control Training Package

The aim of this paper is to present an integrated Internet-based package for teaching the fundamentals of motion control by using a wide range of resources: theory, videos, simulators, games, quizzes, and a remote lab. The package is aimed at automation technicians, pupils at vocational schools and students taking an introductory course in automatic control, and was designed to complement traditional teaching methods and not as a substitute for them. The scope of this package was also chosen to complement the control engineering curriculum. The evaluation data collected from the users suggest that this strategy gave very good results and raised the interest of learners.

Integrating human swarm interaction in a distributed robotic control system

A multi-agent control architecture for swarm robotics applications which includes an innovative human-swarm interface is proposed. The architecture is designed to allow an operator to monitor and guide a robotic swarm to accomplish its missions. The system is composed of three types of agents, a graphical user interface agent, and a pair of a local and a social agent for each robot in the swarm. The local agent implements low level robot-specific functionalities like movement, obstacle avoidance and localization. The control algorithm is implemented in the social agent and is based on an adapted distributed version of the Particle Swarm Optimization technique. An original method, Gravity Points Method, for representing goals which are used by the human-swarm interface is also proposed. Experimental results using simulated e-puck robots are presented and directions for further developments are given.

A new model for interactions between robots in a swarm

Robotic swarms have a great potential to solve in a simple way, without the need for a central controller, a wide range of difficult real-world problems, such as transportation, search and rescue missions etc. While there are important results in what regards the emergence of complex behaviors from very simple interacting robots, the security of robotic swarms remains a problem which did not get the proper consideration. With the overall goal of enabling the full distributed security of a robotic swarm, the contributions of this paper are threefold. First, a bioinspired framework based on membrane computing (P colonies) is proposed for approaching this issue. Secondly, the functionalities of a P colonies simulator are presented and finally, the notion of P swarm is introduced as a relevant new formal model of safe interactions between robots in a swarm.

Evaluation of the Pharmacological Descriptors Related to the Induction of Antidepressant Activity and its Prediction by QSAR/QRAR Methods

Antidepressants are psychiatric agents used for the treatment of different types of depression, being at present amongst the most commonly prescribed drugs, while their effectiveness and adverse effects are still the subject of many studies. To reduce the inefficiency of known antidepressants caused by their side-effects, many research efforts have recently focused on the development of improved strategies for new antidepressants drug design. For this reason it is necessary to apply very fast and precise techniques, such as QSAR (Quantitative Structure-Activity Relationships) and QRAR (Quantitative Retention-Activity Relationship), which are capable to analyze and predict the biological activity for these structures, taking in account the possible changes of the molecular structures and chromatographic parameters. We discuss the pharmaceutical descriptors (van der Waals, electrostatic, hydrophobicity, hydrogen donor/acceptor bond, Verloops parameters, polar area) involved in QSAR and also chromatographic parameters involved in QRAR studies of antidepressants. Antidepressant activities of alkanol piperazine, acetamides, arylpiperazines, thienopyrimidinone derivatives (as preclinical antidepressants) and also the antidepressants already used in clinical practice are mentioned.

Hybrid geno-fuzzy controllers

New methods for designing and analyzing fuzzy controllers are required. Some architectures for integrating genetic algorithms with fuzzy logic controllers, the so called hybrid geno-fuzzy controllers, are introduced and discussed. A new hybrid geno-fuzzy controller based on the algebraic model of the fuzzy controller is proposed. Genetic algorithms are shown to be able to deduce the algebraic model of a simple fuzzy controller used for controlling a truck backer-upper system. The genetic algorithm is further used to tune the coefficients of the deduced algebraic model. The presented results indicate that the hybrid geno-fuzzy controller is superior to a conventional fuzzy controller.