5 Search Results for "Peters, Jan"

Document
DOI: 10.4230/DagRep.5.10.1
Multimodal Manipulation Under Uncertainty (Dagstuhl Seminar 15411)

Authors: Jan Peters, Justus Piater, Robert Platt, and Siddhartha Srinivasa

Published in: Dagstuhl Reports, Volume 5, Issue 10 (2016)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 15411 "Multimodal Manipulation Under Uncertainty". The seminar was organized around brief presentations designed to raise questions and initiate discussions, multiple working groups addressing specific topics, and extensive plenary debates. Section 3 reproduces abstracts of brief presentations, and Section 4 summarizes the results of the working groups.
Cite as

Jan Peters, Justus Piater, Robert Platt, and Siddhartha Srinivasa. Multimodal Manipulation Under Uncertainty (Dagstuhl Seminar 15411). In Dagstuhl Reports, Volume 5, Issue 10, pp. 1-18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{peters_et_al:DagRep.5.10.1,
  author =	{Peters, Jan and Piater, Justus and Platt, Robert and Srinivasa, Siddhartha},
  title =	{{Multimodal Manipulation Under Uncertainty (Dagstuhl Seminar 15411)}},
  pages =	{1--18},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{5},
  number =	{10},
  editor =	{Peters, Jan and Piater, Justus and Platt, Robert and Srinivasa, Siddhartha},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.5.10.1},
  URN =		{urn:nbn:de:0030-drops-56968},
  doi =		{10.4230/DagRep.5.10.1},
  annote =	{Keywords: Robotics, Manipulation, Uncertainty, Perception, Computer vision, Range sensing, Tactile sensing}
}
Document
DOI: 10.4230/DagRep.1.3.67
Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131)

Authors: Jeremy L. Wyatt, Peter Dayan, Ales Leonardis, and Jan Peters

Published in: Dagstuhl Reports, Volume 1, Issue 3 (2011)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 11131 ``Exploration and Curiosity in Robot Learning and Inference''. This seminar was concerned with answering the question: how should a robot choose its actions and experiences so as to maximise the effectiveness of its learning?}. The seminar brought together workers from three fields: machine learning, robotics and computational neuroscience. The seminar gave an overview of active research, and identified open research problems. In particular the seminar identified the difficulties in moving from theoretically well grounded notions of curiosity to practical robot implementations.
Cite as

Jeremy L. Wyatt, Peter Dayan, Ales Leonardis, and Jan Peters. Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131). In Dagstuhl Reports, Volume 1, Issue 3, pp. 67-95, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@Article{wyatt_et_al:DagRep.1.3.67,
  author =	{Wyatt, Jeremy L. and Dayan, Peter and Leonardis, Ales and Peters, Jan},
  title =	{{Exploration and Curiosity in Robot Learning and Inference (Dagstuhl Seminar 11131)}},
  pages =	{67--95},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2011},
  volume =	{1},
  number =	{3},
  editor =	{Wyatt, Jeremy L. and Dayan, Peter and Leonardis, Ales and Peters, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.1.3.67},
  URN =		{urn:nbn:de:0030-drops-31943},
  doi =		{10.4230/DagRep.1.3.67},
  annote =	{Keywords: Artificial Intelligence, Robotics, Learning, Exploration, Curiosity}
}
Document
DOI: 10.4230/OASIcs.KiVS.2011.14
A Reputation-Based Approach to Self-Adaptive Service Selection

Authors: Jan Sudeikat, Wolfgang Renz, Ante Vilenica, and Winfried Lamersdorf

Published in: OASIcs, Volume 17, 17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011)

Abstract
Service-orientation provides concepts and tools for flexible composition and management of largescale distributed software applications. The automated run-time management of such loosely coupled software systems, however, poses still major challenges and is therefore an active research area, including the use of novel computing paradigms. In this context, the dynamic and adaptive selection of best possible service providers is an important task, which can be addressed by an appropriate middleware layer that allows considering different service quality aspects when managing the adaptive execution of distributed service workflows dynamically. In such an approach, service consumers are enabled to delegate the adaptive selection of service providers at run-time to the execution infrastructure. The selection criteria used are based on the cost of a service provision and the continuous, dynamic evaluation of reputations of providers, i.e. maintained track records of meeting the respective service commitments. This paper discusses the design and operating principle of such an automatic service selection middleware extension. Its ability to balance different quality criteria for service selection, such as service cost vs. the reliability of provision, is empirically evaluated based on a multi-agent platform approach.
Cite as

Jan Sudeikat, Wolfgang Renz, Ante Vilenica, and Winfried Lamersdorf. A Reputation-Based Approach to Self-Adaptive Service Selection. In 17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011). Open Access Series in Informatics (OASIcs), Volume 17, pp. 14-25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@InProceedings{sudeikat_et_al:OASIcs.KiVS.2011.14,
  author =	{Sudeikat, Jan and Renz, Wolfgang and Vilenica, Ante and Lamersdorf, Winfried},
  title =	{{A Reputation-Based Approach to Self-Adaptive Service Selection}},
  booktitle =	{17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011)},
  pages =	{14--25},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-27-9},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{17},
  editor =	{Luttenberger, Norbert and Peters, Hagen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.KiVS.2011.14},
  URN =		{urn:nbn:de:0030-drops-29540},
  doi =		{10.4230/OASIcs.KiVS.2011.14},
  annote =	{Keywords: Service, Workflow, Multagent System, Self-Adaptivity}
}
Document
DOI: 10.4230/DagSemProc.09341.1
09341 Abstracts Collection – Cognition, Control and Learning for Robot Manipulation in Human Environments

Authors: Michael Beetz, Oliver Brock, Gordon Cheng, and Jan Peters

Published in: Dagstuhl Seminar Proceedings, Volume 9341, Cognition, Control and Learning for Robot Manipulation in Human Environments (2010)

Abstract
From 16.08. to 21.08.2009, the Dagstuhl Seminar 09341 ``Cognition, Control and Learning for Robot Manipulation in Human Environments '' was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Michael Beetz, Oliver Brock, Gordon Cheng, and Jan Peters. 09341 Abstracts Collection – Cognition, Control and Learning for Robot Manipulation in Human Environments. In Cognition, Control and Learning for Robot Manipulation in Human Environments. Dagstuhl Seminar Proceedings, Volume 9341, pp. 1-16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{beetz_et_al:DagSemProc.09341.1,
  author =	{Beetz, Michael and Brock, Oliver and Cheng, Gordon and Peters, Jan},
  title =	{{09341 Abstracts Collection – Cognition, Control and Learning for Robot Manipulation in Human Environments}},
  booktitle =	{Cognition, Control and Learning for Robot Manipulation in Human Environments},
  pages =	{1--16},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9341},
  editor =	{Michael Beetz and Oliver Brock and Gordon Cheng and Jan Peters},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09341.1},
  URN =		{urn:nbn:de:0030-drops-23663},
  doi =		{10.4230/DagSemProc.09341.1},
  annote =	{Keywords: Mobile manipulation, cognition, control, learning, humanoid robot, unstructured environments}
}
Document
DOI: 10.4230/DagSemProc.09341.2
09341 Summary – Cognition, Control and Learning for Robot Manipulation in Human Environments

Authors: Michael Beetz, Oliver Brock, Gordon Cheng, and Jan Peters

Published in: Dagstuhl Seminar Proceedings, Volume 9341, Cognition, Control and Learning for Robot Manipulation in Human Environments (2010)

Abstract
High performance robot arms are faster, more accurate, and stronger than humans. Yet many manipulation tasks that are easily performed by humans as part of their daily life are well beyond the capabilities of such robots. The main reason for this superiority is that humans can rely upon neural information processing and control mechanisms which are tailored for performing complex motor skills, adapting to uncertain environments and to not imposing a danger to surrounding humans. As we are working towards autonomous service robots operating and performing manipulation in the presence of humans and in human living and working environments, the robots must exhibit similar levels of flexibility, compliance, and adaptivity. The goal of this Dagstuhl seminar is to make a big step towards pushing robot manipulation forward such that robot assisted living can become a concrete vision for the future. In order to achieve this goal, the computational aspects of everyday manipulation tasks need to be well-understood, and requires the thorough study of the interaction of perceptual, learning, reasoning, planning, and control mechanisms. The challenges to be met include cooperation with humans, uncertainty in both task and environments, real-time action requirements, and the use of tools. The challenges cannot be met by merely improving the software engineering and programming techniques. Rather the systems need built-in capabilities to deal with these challenges. Looking at natural intelligent systems, the most promising approach for handling them is to equip the systems with more powerful cognitive mechanisms. The potential impact of bringing cognition, control and learning methods together for robotic manipulation can be enormous. This urge for such concerted approaches is reflected by a large number of national and international research initiatives including the DARPA cognitive systems initiative of the Information Processing Technoloy Office, various integrated projects funded by the European Community, the British Foresight program for cognitive systems, huge Japanese research efforts, to name only a few. As a result, many researchers all over the world engage in cognitive system research and there is need for and value in discussion. These discussions become particularly promising because of the growing readiness of researchers of different disciplines to talk to each other. Early results of such interdisciplinary crossfertilization can already be observed and we only intend to give a few examples: Cognitive psychologists have presented empirical evidence for the use of Bayesian estimation and discovered the cost functions possibly underlying human motor control. Neuroscientists have shown that reinforcement learning algorithms can be used to explain the role of Dopamine in the human basal ganglia as well as the functioning of the bea brain. Computer scientists and engineers have shown that the understanding of brain mechanisms can result into realiable learning algorithms as well as control setups. Insights from artificial intelligence such as Bayesian networks and the associated reasoning and learning mechanisms have inspired research in cognitive psychology, in particular the formation of causal theory in young children. These examples suggest that (1)~successful computational mechanisms in artificial cognitive systems tend to have counterparts with similar functionality in natural cognitive systems; and (2)~new consolidated findings about the structure and functional organization of perception and motion control in natural cognitive systems indicate in a number of cases much better ways of organizing and specifying computational tasks in artificial cognitive systems.
Cite as

Michael Beetz, Oliver Brock, Gordon Cheng, and Jan Peters. 09341 Summary – Cognition, Control and Learning for Robot Manipulation in Human Environments. In Cognition, Control and Learning for Robot Manipulation in Human Environments. Dagstuhl Seminar Proceedings, Volume 9341, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{beetz_et_al:DagSemProc.09341.2,
  author =	{Beetz, Michael and Brock, Oliver and Cheng, Gordon and Peters, Jan},
  title =	{{09341 Summary – Cognition, Control and Learning for Robot Manipulation in Human Environments}},
  booktitle =	{Cognition, Control and Learning for Robot Manipulation in Human Environments},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2010},
  volume =	{9341},
  editor =	{Michael Beetz and Oliver Brock and Gordon Cheng and Jan Peters},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.09341.2},
  URN =		{urn:nbn:de:0030-drops-23647},
  doi =		{10.4230/DagSemProc.09341.2},
  annote =	{Keywords: Mobile manipulation, cognition, control, learning, humanoid robot, unstructured environments}
}
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