Henrik Hautop Lund

Bio: Henrik Hautop Lund is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: Modular design & Self-reconfiguring modular robot. The author has an hindex of 30, co-authored 159 publications receiving 3740 citations. Previous affiliations of Henrik Hautop Lund include University of Southern Denmark & Academy of Fine Arts, Helsinki.

Evolving mobile robots in simulated and real environments

Abstract: The problem of the validity of simulation is particularly relevant for methodologies that use machine learning techniques to develop control systems for autonomous robots, as, for instance, the artificial life approach known as evolutionary robotics. In fact, although it has been demonstrated that training or evolving robots in real environments is possible, the number of trials needed to test the system discourages the use of physical robots during the training period. By evolving neural controllers for a Khepera robot in computer simulations and then transferring the agents obtained to the real environment we show that (a) an accurate model of a particular robot-environment dynamics can be built by sampling the real world through the sensors and the actuators of the robot; (b) the performance gap between the obtained behaviors in simulated and real environments may be significantly reduced by introducing a "conservative" form of noise; (c) if a decrease in performance is observed when the system is transferred to a real environment, successful and robust results can be obtained by continuing the evolutionary process in the real environment for a few generations.

Modular ATRON: modules for a self-reconfigurable robot

Abstract: This paper describes the mechanical and electrical design of a new lattice based self-reconfigurable robot, called the ATRON. The ATRON system consists of several fully self-contained robot modules, each having their own processing power, power supply, sensors and actuators. The ATRON modules are roughly spheres with equatorial rotation. Each module can be connected to up to eight neighbors through four male and four female connectors. In this paper, we describe the realization of the design, both the mechanics and the electronics. Details on power sharing and power consumption is given. Finally, this paper includes a brief outline of our future work on the ATRON system.

Design of the ATRON lattice-based self-reconfigurable robot

Abstract: Self-reconfigurable robots are robots that can change their shape in order to better suit their given task in their immediate environment. Related work on around fifteen such robots is presented, compared and discussed. Based on this survey, design considerations leading to a novel design for a self-reconfigurable robot, called "ATRON", is described. The ATRON robot is a lattice-based self-reconfigurable robot with modules composed of two hemispheres joined by a single revolute joint. Mechanical design and resulting system properties are described and discussed, based on FEM analyses as well as real-world experiments. It is concluded that the ATRON design is both competent and novel. Even though the ATRON modules are minimalistic, in the sense that they have only one actuated degree of freedom, the collective of modules is capable of self-reconfiguring in three dimensions. Also, a question is raised on how to compare and evaluate designs for self-reconfigurable robots, with a focus on lattice-based systems.

T helper cell type 1 (Th1), Th2 and Th17 responses to myelin basic protein and disease activity in multiple sclerosis.

Abstract: Autoreactive T cells are thought to play an essential role in the pathogenesis of multiple sclerosis (MS). We examined the stimulatory effect of human myelin basic protein (MBP) on mononuclear cell (MNC) cultures from 22 patients with MS and 22 sex-matched and age-matched healthy individuals, and related the patient responses to disease activity, as indicated by magnetic resonance imaging. The MBP induced a dose-dependent release of interferon-gamma (IFN-gamma), tumour necrosis factor-alpha (TNF-alpha) and interleukin-10 (IL-10) by patient-derived MNCs. The patients' cells produced higher amounts of IFN-gamma and TNF-alpha, and lower amounts of IL-10, than cells from healthy controls (P<0.03 to P<0.04). Five patients with MS and no controls, displayed MBP-induced CD4+ T-cell proliferation. These high-responders exhibited enhanced production of IL-17, IFN-gamma, IL-5 and IL-4 upon challenge with MBP, as compared with the remaining patients and the healthy controls (P<0.002 to P<0.01). A strong correlation was found between the MBP-induced CD4+ T-cell proliferation and production of IL-17, IFN-gamma, IL-5 and IL-4 (P<0.0001 to P<0.01) within the patient group, and the production of IL-17 and IL-5 correlated with the number of active plaques on magnetic resonance images (P=0.04 and P=0.007). These data suggest that autoantigen-driven CD4+ T-cell proliferation and release of IL-17 and IL-5 may be associated with disease activity. Larger studies are needed to confirm this.

The Physical Effect of Exergames in Healthy Elderly-A Systematic Review.

Abstract: Exergames have been suggested as an innovative approach to enhance physical activity in the elderly. The objective of this review was to determine the effectiveness of exergames on validated quantitative physical outcomes in healthy elderly individuals. We used Centre for Review and Disseminations guidance to conduct systematic reviews. Four electronic databases were searched. We included randomized controlled trials (RCTs), the study participants were healthy elderly individuals, and the intervention of interest was exergaming. The title and abstract screening of the 1861 citations identified 36 studies as potentially eligible for this review, and an additional nine were identified from reference lists. The full text screening identified seven studies with a total of 311 participants, all reporting RCTs with low-to-moderate methodological quality. Six of the seven studies found a positive effect of exergaming on the health of the elderly. However, the variation of intervention approaches and out...

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Human cognitive abilities: A survey of factor analytic studies

Abstract: (1998). Human cognitive abilities: A survey of factor analytic studies. Gifted and Talented International: Vol. 13, No. 2, pp. 97-98.

Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation

Abstract: We survey the research on interactive evolutionary computation (IEC). The IEC is an EC that optimizes systems based on subjective human evaluation. The definition and features of the IEC are first described and then followed by an overview of the IEC research. The overview primarily consists of application research and interface research. In this survey the IEC application fields include graphic arts and animation, 3D computer graphics lighting, music, editorial design, industrial design, facial image generation, speed processing and synthesis, hearing aid fitting, virtual reality, media database retrieval, data mining, image processing, control and robotics, food industry, geophysics, education, entertainment, social system, and so on. The interface research to reduce human fatigue is also included. Finally, we discuss the IEC from the point of the future research direction of computational intelligence. This paper features a survey of about 250 IEC research papers.