| 1. |
- Bouguerra, Abdelbaki, et al.
(author)
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Hierarchical task planning under uncertainty
- 2004
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Conference paper (peer-reviewed)abstract
- In this paper we present an algorithm for planning in non-deterministic domains. Our algorithm C-SHOP extends the successful classical HTN planner SHOP, by introducing new mechanisms to handle situations where there is incomplete and uncertain information about the state of the environment. Being an HTN planner, C-SHOP supports coding domain-dependent knowledge in a powerful way that describes how to solve the planning problem.To handle uncertainty, belief states are used to represent incomplete information about the state of the world, and actions are allowed to have stochastic outcomes. This allows our algorithm to solve problems involving partial observability through feedback at execution time. We outline the main characteristics of the algorithm, and present performance results on some problems found in literature.
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| 2. |
- Broxvall, Mathias, et al.
(author)
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Have another look on failures and recovery planning in perceptual anchoring
- 2004
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Conference paper (peer-reviewed)abstract
- An important requirement for autonomous systems is the ability to detect and recover from exceptional situations such as failures in observations. In this paper we demonstrate how techniques for planning with sensing under uncertainty can play a major role in solving the problem of recovering from such situations. In this first step we concentrate on failures in perceptual anchoring, that is how to connect a symbol representing an object to the percepts of that object. We provide a classification of failures and present planning-based methods for recovering from them. We illustrate our approach by showing tests run on a mobile robot equipped with a color camera.
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| 3. |
- Broxvall, Mathias, et al.
(author)
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Steps toward detecting and recovering from perceptual failures
- 2004
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In: Proceedings of the 8th international conference on intelligent autonomous systems. ; , s. 793-800
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Conference paper (peer-reviewed)abstract
- An important requirement for autonomous systems is the ability to detect and recover from exceptional situations such as failures in observations. In this paper we investigate how traditional AI planning techniques can be used to reason about observations and to recover from these situations. In this first step we concentrate on failures in perceptual anchoring. We illustrate our approach by showing experiments run on a mobile robot equipped with a color camera.
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| 4. |
- Coradeschi, Silvia, et al.
(author)
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Fuzzy anchoring
- 2001
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In: The 10th IEEE international conference on fuzzy systems. - 078037293X ; , s. 111-114
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Conference paper (peer-reviewed)abstract
- An intelligent physical agent must incorporate motor and perceptual processes to interface with the physical world, and abstract cognitive processes to reason about the world and the options available. One crucial aspect of incorporating cognitive processes into a physically embedded reasoning system is the integration between the symbols used by the reasoning processes to denote physical objects, and the perceptual data corresponding to these objects. We treat this integration aspect by proposing a fuzzy computational theory of anchoring. Anchoring is the process of creating and maintaining the correspondence between symbols and percepts that refer to the same physical objects. Modeling this process using fuzzy set-theoretic notions enables dealing with perceptual data that can be affected by uncertainty/imprecision and imprecise/vague linguistic descriptions of objects
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| 5. |
- Karlsson, Lars
(author)
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Conditional progressive planning under uncertainty
- 2001
-
Conference paper (peer-reviewed)abstract
- In this article, we describe a possibilis - tic/probabilistic conditional planner called PTLplan Being inspired by Bacchus and Ka - banza's TLplan, PTLplan is a progressive planner that uses strategic knowledge encoded in a tem - poral logic to reduce its search space Actions effects and sensing can be context dependent and uncertain, and the information the planning agent has at each point in time is represented as a set of situations with associated possibilities or probabilities Besides presenting the planner itself - its representation of actions and plans, and its algorithm - we also provide some promising data from performance tests
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| 6. |
- Karlsson, Lars, et al.
(author)
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Progressive planning for mobile robots : a progress report
- 2002
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In: Advances in Plan-Based Control of Robotic Agents. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 3540001689 ; , s. 273-297
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Conference paper (peer-reviewed)abstract
- In this article, we describe a possibilistic/probabilistic conditional planner called PTLplan, and how this planner can be integrated with a behavior-based fuzzy control system called the Thinking Cap in order to execute the generated plans. Being inspired by Bacchus and Kabanza's TLplan, PTLplan is a progressive planner that uses strategic knowledge encoded in a temporal logic to reduce its search space. Actions' effects and sensing can be context dependent and uncertain, and the resulting plans may contain conditional branches. When these plans are executed by the control system, they are transformed into B-plans which essentially are combinations of fuzzy behaviors to be executed in different contexts
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| 7. |
- Loutfi, Amy, et al.
(author)
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Putting olfaction into action : using an electronic nose on an multi-sensing mobile robot
- 2004
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In: Proceedings of the 2004 IEEE/RSJ international conference on intelligent robots and systems (IROS 2004). - 0780384636 ; , s. 337-342
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Conference paper (peer-reviewed)abstract
- Olfaction is a challenging new sensing modality for intelligent systems. With the emergence of electronic noses it is now possible to detect and recognise a range of different odours for a variety of applications. An existing application is to use electronic olfaction on mobile robots for the purpose of odour based navigation. In this work, we introduce a new application where electronic olfaction is used in cooperation with other types of sensors on a mobile robot in order to acquire the odour
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| 8. |
- Lundh, Robert, et al.
(author)
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Dynamic configuration of a team of robots
- 2004
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In: Proceedings of the ECAI-04 workshop on agents in dynamic and real-time environments. ; , s. 57-62
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Conference paper (peer-reviewed)abstract
- We study teams of autonomous robotic agents in which agents can help each other by offering information-producing resources and functionalities. Depending on the current situation and tasks, the team may need to change its functional configuration, that is, which agents provide which functionalities to whom. We propose to use knowledge-based techniques to automatically synthesize new team configurations in response to changes in the situation or tasks. This note summarizes our approach, and reports our preliminary steps in this direction.
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| 9. |
- Pettersson, Ola, et al.
(author)
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Model-free execution monitoring in behavior-based mobile robotics
- 2003
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Conference paper (peer-reviewed)abstract
- In this paper we present a model-free execution monitor for behavior-based mobile robots. By model-free we mean that the monitoring is based only on the actual execution, without involving any predictive models of the controlled system. Model-free monitors are especially suitable for systems where it is hard to obtain adequate models. In our approach we analyze the activation levels of the different behaviors using a pattern recognition technique. Our model-free execution monitor, which is realized by radial basis function networks, is shown to give a high performance in several realistic simulations.
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| 10. |
- Pettersson, Ola, 1972-
(author)
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Model-free execution monitoring in behavior-based mobile robotics
- 2004
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Doctoral thesis (other academic/artistic)abstract
- In the near future, autonomous mobile robots are expected to assist us by performing service tasks in many different areas, including transportation, cleaning, mining, or agriculture. In order to manage these tasks in a changing and partially unpredictable environment, without the help of humans, the robot must have the ability to plan its actions and to execute them robustly and in a safe way. Since the real world is dynamic and not fully predictable, the robot must also have the ability to detect when the execution does not proceed as planned, and to correctly identify the causes of the failure. An execution monitoring system is a system that allows the robot to detect and classify these failures. Most current approaches to execution monitoring in robotics are based on the idea of predicting the outcomes of the robot's actions by using some sort of model, and comparing the predicted outcomes with the observed ones. In contrary, this thesis explores the use of model-free approaches to execution monitoring, that is, approaches that do not use predictive models. These approaches solely observe the actual execution of the robot, and detect certain patterns that indicate a problem. In this thesis, we show that pattern recognition techniques can be applied to realize model-free execution monitoring by classifying observed behavioral patterns into normal or faulty behaviors. We investigate the use of several such techniques, and verify their utility in a number of experiments involving the navigation of a mobile robot in indoor environments. Statistical measures are used to compare the results given from several realistic simulations. Our approach has also been successfully tested on a real robot navigating in an office environment. Interesting, this test has shown that we can train a model-free execution monitor in simulation, and then use it in a real robot.
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