The Parameter-Less Self-Organizing Map algorithm

The Parameter-Less Self-Organizing Map (PLSOM) is a new neural network algorithm based on the Self-Organizing Map (SOM). It eliminates the need for a learning rate and annealing schemes for learning rate and neighbourhood size. We discuss the relative performance of the PLSOM and the SOM and demonstrate some tasks in which the SOM fails but the PLSOM performs satisfactory. Finally we discuss some example applications of the PLSOM and present a proof of ordering under certain limited conditions.Comment: 29 pages, 27 figures. Based on publication in IEEE Trans. on Neural Network

Issues in the Scalability of Gate-level Morphogenetic Evolvable Hardware

Traditional approaches to evolvable hardware (EHW), in which the field programmable gate array (FPGA) configuration is directly encoded, have not scaled well with increasing circuit and FPGA complexity. To overcome this there have been moves towards encoding a growth process, known as morphogenesis. Using a morphogenetic approach, has shown success in scaling gate-level EHW for a signal routing problem, however, when faced with a evolving a one-bit full adder, unforseen difficulties were encountered. In this paper, we provide a measurement of EHW problem difficulty that takes into account the salient features of the problem, and when combined with a measure of feedback from the fitness function, we are able to estimate whether or not a given EHW problem is likely to be able to be solved successfully by our morphogenetic approach. Using these measurements we are also able to give an indication of the scalability of morphogenesis when applied to EHW

Induction of Topological Environment Maps from Sequences of Visited Places

In this paper we address the problem of topologically mapping environments which contain inherent perceptual aliasing caused by repeated environment structures. We propose an approach that does not use motion or odometric information but only a sequence of deterministic measurements observed by traversing an environment. Our algorithm implements a stochastic local search to build a small map which is consistent with local adjacency information extracted from a sequence of observations. Moreover, local adjacency information is incorporated to disambiguate places which are physically different but appear identical to the robots senses. Experiments show that the proposed method is capable of mapping environments with a high degree of perceptual aliasing, and that it infers a small map quickly

The Mini-Robot Khepera as a Foraging Animate: Synthesis and Analysis of Behaviour

Löffler A, Klahold J, Rückert U. The Mini-Robot Khepera as a Foraging Animate: Synthesis and Analysis of Behaviour. In: Rückert U, Sitte J, Witkowski U, eds. Proceedings of the 5th International Heinz Nixdorf Symposium: Autonomous Minirobots for Research and Edutainment (AMiRE01). Vol 97. Paderborn, Germany: Heinz Nixdorf Institut, Universität Paderborn; 2001: 93-130.The work presented in this paper deals with the development of a methodology for resource-efficient behaviour synthesis on autonomous systems. In this context, a definition of a maximal problem with respect to the resources of a given system is introduced. It is elucidated by means of an exemplary implementation of the solution to such a problem using the mini-robot Khepera as the experimental platform. The described task consists of exploring an unknown and dynamically changing environment, collecting and transporting objects, which are associated with light-sources, and navigating to a home-base. The critical point is represented by the accumulated positioning errors in odometrical path-integration due to slippage. Therefore, adaptive sensor calibration using a specific variant of Kohonen’s algorithm is applied in two cases to extract symbolic, e.g. geometric, information from the sub-symbolic sensor data, which is used to enhance position control by landmark mapping and orientation. In order to successfully handle the arising complex interactions, a heterogeneous control-architecture based on a parallel implementation of basic behaviours coupled by a rule-based central unit is proposed

Morphogenetic Evolvable Hardware Controllers for Robot Walking

We propose to develop reactive robot leg controllers in hardware using a morphogenetic approach that incorporates both evolutionary and developmental processes. Evolvable hardware has been crippled by issues of scalability and viability of evolved designs that arise when evolving complex circuits on modern mainstream field programmable gate arrays (FPGAs). To overcome these limitations requires a shift away from direct encodings of the FPGA configuration to encoding a growth process, morphogenesis, thus moving the complexity from the genotype to the genotype-phenotype mapping. Although a few researchers have attempted this, how to successfully apply morphogenesis to evolvable hardware still remains an open question

Demand-compliant design

In this paper, we describe, in detail, a design method that assures that the designed product satisfies a set of prescribed demands while, at the same time, providing a concise representation of the design that facilitates communication in multidisciplinary design teams. This Demand Compliant Design (DeCoDe) method was in itself designed to comply with a set of demands. The demands on the method were determined by an analysis of some of the most widely used design methods and from the needs arising in the practice of design for quality. We show several modes of use of the DeCoDe method and illustrate with examples

Designing a Morphogenetic System for Evolvable Hardware

Traditional approaches to evolvable hardware (EHW), using a direct encoding, have not scaled well with increases in problem complexity. To overcome this there have been moves towards encoding a growth process, which however have not shown a great deal of success to date. In this paper we present the design of a morphogenetic EHW model that has taken the salient features of biological processes and structures to produce an evolutionary and growth model that consistently outperforms a traditional EHW approach using a direct encoding, and scales well to larger, more complex, problems

Methodic Design of Robot Vision Systems

In this paper we use the design of an innovative on-board vision system for a small commercial minirobotto demonstrate the application of a demand compliant design (DeCoDe) method. Vision systems are amongst the most complex sensor systems both in nature and in engineering and thus provide an excellent arena for testing design methods. A review of current design methods for mechatronic systems shows that there are no methods that support or require a complete description of the product system. The DeCoDe method is a step towards overcoming this deflciencty. The minirobot robot design is carried from the generic vision system level down to first refinement for a minirobot vision system for visual navigation

Gate-Level Morphogenetic Evolvable Hardware for Scalability and Adaptation on FPGAs

Traditional approaches to evolvable hardware (EHW), in which the field programmable gate array (FPGA) configuration is directly encoded, have not scaled well with increasing circuit and FPGA complexity. To overcome this there have been moves towards encoding a growth process, known as morphogenesis, however existing approaches have tended to abstract away the underlying FPGA architecture. Although currently commercially available FPGAs are not the most evolution-friendly platforms, having complex architectures and issues with potentially damaging configurations, evolving circuits on commercially available devices without requiring a move to high-level building blocks is a necessary prerequisite for the adoption of EHW to solving real problems in electronic design, repair and adaptation. In this paper we present a morphogenetic EHW model where growth is directed by the gate-level state of the FPGA. We demonstrate that this approach consistently outperforms a traditional EHW approach using a direct encoding, in the number of generations required to find an optimal solution, and in its ability to scale to increases in circuit size and complexity. Issues in EHW problem solvability are also identified, and preliminary work is presented showing that a morphogenetic approach to EHW may be well suited to correcting damaged circuits

Family System: A Reference Model for Developing Home Automation Applications

This research is a pioneer attempt to establish theoretical foundation and a framework for technical developments in Home Automation. This study suggests the need for an International Technology Roadmap for Home Automation (ITRHA) to formulate a need based vision of typically 10 to 15 years and stresses the need for HA to cater for the specific requirements of family home users. The concept of Family Life Cycle is used to understand the temporal needs of family. In order to formally describe a coherent set of family processes, their relationships, and interaction with external elements, a reference model named Family System is established that identifies External Entities, 7 major processes, and 7 subsystems to manage smooth functioning of these processes by allocating resources and interfacing between processes and External Entities. The Family System reference model can be used to conduct detailed requirement analysis and thus identify potential HA products and services meeting realistic user needs