| 1. |
- Civera, Javier, et al.
(author)
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Special Issue on Cloud Robotics and Automation
- 2015
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In: IEEE Transactions on Automation Science and Engineering. - : IEEE Press. - 1545-5955 .- 1558-3783. ; 12:2, s. 396-397
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Journal article (other academic/artistic)abstract
- The articles in this special section focus on the use of cloud computing in the robotics industry. The Internet and the availability of vast computational resources, ever-growing data and storage capacity have the potential to define a new paradigm for robotics and automation. An intelligent system connected to the Internet can expand its onboard local data, computation and sensors with huge data repositories from similar and very different domains, massive parallel computation from server farms and sensor/actuator streams from other robots and automata. It is the potential and also the research challenges of the field that become the focus on this special section. The goal is to group together and to show the state-of-the-art of this newly emerged field, identify the relevant advances and topics, point out the current lines of research and potential applications, and discuss the main research challenges and future work directions.
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| 2. |
- Hanheide, Marc, et al.
(author)
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Robot task planning and explanation in open and uncertain worlds
- 2015
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In: Artificial Intelligence. - : Elsevier. - 0004-3702 .- 1872-7921.
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Journal article (peer-reviewed)abstract
- A long-standing goal of AI is to enable robots to plan in the face of uncertain and incomplete information, and to handle task failure intelligently. This paper shows how to achieve this. There are two central ideas. The first idea is to organize the robot's knowledge into three layers: instance knowledge at the bottom, commonsense knowledge above that, and diagnostic knowledge on top. Knowledge in a layer above can be used to modify knowledge in the layer(s) below. The second idea is that the robot should represent not just how its actions change the world, but also what it knows or believes. There are two types of knowledge effects the robot's actions can have: epistemic effects (I believe X because I saw it) and assumptions (I'll assume X to be true). By combining the knowledge layers with the models of knowledge effects, we can simultaneously solve several problems in robotics: (i) task planning and execution under uncertainty; (ii) task planning and execution in open worlds; (iii) explaining task failure; (iv) verifying those explanations. The paper describes how the ideas are implemented in a three-layer architecture on a mobile robot platform. The robot implementation was evaluated in five different experiments on object search, mapping, and room categorization.
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