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2008 ecsis symposium on learning and adaptive behaviors for robotic systems, lab-rs 2008

ISBN: (纸本)9780769532721

The proceedings contain 19 papers. The topics discussed include: mixture model segmentation for gait recognition;what is an appropriate theory of limitation for a robot learner?;drumming with a humanoid robot: results from human-robot interaction studies;movement times in inter- and intrapersonal human coordination;improving robotic system robustness via a generalised formal artificial neural system;scalable biologically inspired neural networks with spike time based learning;recurrent neural associative learning of forward and inverse kinematics for movement generation of the redundant PA-10 robot;evolvability of neuromodulated learning for robots;learning vision algorithms for real mobile robots with genetic programming;towards object classification using 3D sensor data;learning robot dynamics for computed torque control using local Gaussian processes regression;and surprise-based learning for developmental robotics.

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Proceedings of the 2008 ecsis symposium on learning and adaptive behaviors for robotic systems, lab-rs 2008: Preface

Proceedings of the 2008 ECSIS Symposium on Learning and Adap...

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Proceedings of the 2008 ecsis symposium on learning and adaptive behaviors for robotic systems, lab-rs 2008 2008年 vii页

作者： Stoica, Adrian Tunstel, Eddie Huntsberger, Terry Arslan, Tughrul Vijayakumar, Sethu El-Rayis, Ahmed O. ECSIS/UoE/JPL Applied Physics Laboratory John Hopkins University United States NASA Jet Propulsion Laboratory United States University of Edinburgh United Kingdom

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ISBN: (纸本)9780769532721

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Monitoring Strategies for adaptive Periodic Control in Behavior-based robotic systems

Monitoring Strategies for Adaptive Periodic Control in Behav...

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ecsis symposium on Advanced Technologies for Enhanced Quality of Life (AT-EQUAL 2009)

作者： Burattini, Ernesto Finzi, Alberto Rossi, Silvia Staffa, Mariacarla Univ Naples Federico II Dipartimento Sci Fisiche Naples Italy Univ Naples Federico II Dipartimento Informat & Sistemist Naples Italy

ISBN: (纸本)9780769537535

The main goal of our current research is the design of a behavior-based robotic architecture that has the capability of adapting its behaviors to the rate of change of both the environment and its internal states reducing the computational costs of input processing. Inspired by research on biological clocks, we introduced a simple schema theory model where releasing mechanisms are combined with adaptive internal clocks. In this paper, we describe the design and development of a complete robotic architecture implementing this model. In particular, we considered a mobile robot domain that simulates the navigation behavior of a Catagliphys ant enhanced with simple visual capabilities.

关键词： Mobile robots

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Improving the Quality of Life of People with Dementia through the Use of Socially Assistive Robots

Improving the Quality of Life of People with Dementia throug...

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ecsis symposium on Advanced Technologies for Enhanced Quality of Life (AT-EQUAL 2009)

作者： Tapus, Adriana ENSTA ParisTech Dept Comp Sci Cognit Robot Lab Paris France

ISBN: (纸本)9780769537535

In less than 25 years, 37 million people are expected to have dementia and/or Alzheimer's disease. This significant figure is a result of several factors, including increasing life expectancy and an ageing population in developing countries. Alzheimer's disease, a form of dementia, is a progressive brain disorder that causes memory loss, and behavior and personality changes. People suffering from this disease become increasingly physically and cognitively impaired;they usually need help with all aspects of daily living. While there is currently no cure for dementia, special therapies (e.g., arts and crafts, music therapy) can help people with dementia to live as good a life as possible. We propose to use socially assistive robots as customized/individualized helpers as a complement to humans. This work proposes a new adaptive socially assistive robotic (SAR) system that aims to provide a customized protocol through motivation, encouragement, and companionship for users suffering from cognitive changes related to aging and/or Alzheimer's disease. The robot aims to maintain/improve the user's cognitive attention in a cognitive music game setup.

关键词： socially assistive robotics customized robotic therapy learning and behavior adaptation

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A novel information measure for adaptive controllers in swarm systems

A novel information measure for adaptive controllers in swar...

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ecsis symposium on Advanced Technologies for Enhanced Quality of Life (AT-EQUAL 2009)

作者： Di Prodi, Paolo Porr, Bernd Woergoetter, Florentin Univ Glasgow Intelligent Syst Grp Glasgow Lanark Scotland Berstein Ctr Computat Neurosci Gottingen Germany

ISBN: (纸本)9780769537535

In this work we have developed an information measure called maxcorr suitable for closed loop controllers that makes use of temporal unsupervised learning. It is novel because is computed at the input side of the controller and consider the semantic value of signals, rather then being based on the non semantic approach of Shannon's entropy. The maxcorr can be applied to individual agents to estimate their learning ability, but most importantly to social swarms where agents are learning all the time to achieve a common goal. Indeed in a social system all agents learn at the same time thus being unpredictable. However maxcorr quantitatively explains how agents of a social system select information to make the closed loop model more predictable. Results are compatible with the Luhmann's theory of social differentiation.

关键词： information theory closed loop adaptive controllers social systems

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robotic Scaffolds for Tissue Engineering and Organ Growth

Robotic Scaffolds for Tissue Engineering and Organ Growth

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ecsis symposium on Advanced Technologies for Enhanced Quality of Life (AT-EQUAL 2009)

作者： Stoica, Adrian CALTECH Jet Prop Lab Pasadena CA 91125 USA

ISBN: (纸本)9780769537535

This paper proposes a robotics perspective to the design and analysis of future smart scaffolds to be used in tissue engineering and organ growth. Current biocompatible/biodegradable scaffolds provide load support, template for cell growth, and drug delivery for growth control. It is argued that future scaffolds would benefit from being able to allow/use relative movement among their components, which provides benefits by (I) improving mechanical stress of the cells, proven to stimulate better tissue growth, and (2) offering adaptive characteristics, as a platform that cars (a) reconfigure shape (h) modify size to accommodate beneficial organ development, and (c) guide timed growth of complex organ structures, as well as other controlled changes over lifetime;these would become programmable scaffolds or in-vivo reconfigurable scaffolds. In addition, these may be able to sense their milieu/environment (measure and interpret physical and chemical data in-vivo), compute (to determine optimal movements and drug release) and engage in communications (correlating actions with other tissue/organs, interacting with outside the body instrumentation). Thus, future scaffolds can be treated as robots, of a new class, with specific characteristics and challenges such as being made of biodegradable components, and operating within human body;a robotics system perspective is useful in designing, producing and operating such systems.

关键词： robotics

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Improving robotic system robustness via a generalised formal artificial neural system

Improving robotic system robustness via a generalised formal...

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ecsis symposium on learning and adaptive behaviors for robotic systems

作者： Howells, Gareth Sirlantzis, Konstantinos Univ Kent Dept Elect Canterbury Kent England

ISBN: (纸本)9780769532721

A major concern for robotic guidance systems is that a temporary or permanent failure of a given sensor within the system will erroneously trigger a potential system failure state. This paper introduces a generalised artificial neural system which is capable of addressing such problems by means of the inclusion of a weight value able to incorporate a distinct failure value. This will serve to significantly improve the performance and reliability of the guidance system.

关键词： systems engineering

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Scalable biologically inspired neural networks with spike time based learning

Scalable biologically inspired neural networks with spike ti...

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ecsis symposium on learning and adaptive behaviors for robotic systems

作者： Long, Lyle N. Penn State Univ University Pk PA 16802 USA

ISBN: (纸本)9780769532721

This paper describes the software and algorithmic issues involved in developing scalable large-scale biologically-inspired spiking neural networks. These neural networks are useful in object recognition and signal processing tasks, but will also be useful in simulations to help understand the human brain. The software is written using object oriented programming and is very general and usable for processing a wide range of sensor data and for data fusion.

关键词： Object oriented programming

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Evolvability of neuromodulated learning for robots

Evolvability of neuromodulated learning for robots

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ecsis symposium on learning and adaptive behaviors for robotic systems

作者： Duerr, Peter Mattiussi, Claudio Soltoggio, Andrea Floreano, Dario Ecole Polytech Fed Lausanne Lab Intelligent Syst CH-1015 Lausanne Switzerland Univ Birmingham Sch Comp Sci Birmingham B15 2TT W Midlands England

ISBN: (纸本)9780769532721

Neuromodulation is thought to he one of the underlying principles of learning and memory in biological neural networks. Recent experiments have shown that neuroevolutionary methods benefit from neuromodulation in simple grid-world problems. In this paper we investigate the performance of a neuroevolutionary method applied to a more realistic robotic task. While confirming the favorable effect of neuromodulatory structures, our results indicate that the evolution of such architectures requires a mechanism which allows for selective modular targetting of the neuromodulatory connections.

关键词： Neural networks

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Surprise-based learning for developmental robotics

Surprise-based learning for developmental robotics

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ecsis symposium on learning and adaptive behaviors for robotic systems

作者： Ranasinghe, Nadeesha Shen, Wei-Min Univ So Calif Inst Informat Sci Los Angeles CA 90089 USA

ISBN: (纸本)9780769532721

This paper presents a learning algorithm called surprise-based learning (SBL) capable (of providing physical robot the ability to ataonomonsly learn and plan in an unknown environment without any prior knowledge of its actions or their impact on the environment. This is achieved by creating a model of the environment using prediction rules. A prediction rule describes the observations of the environment prior to the execution of an action and the forecasted or predicted observation of the environment after the action. The algorithm learns by investigating "surprises", which are inconsistencies between the predictions and observed outcome. SBL has been successfully demonstrated on a Modular robot learning and navigating in a small static environment.

关键词： learning algorithms

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