| 1. |
- Bouguerra, Abdelbaki, et al.
(författare)
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Active execution monitoring using planning and semantic knowledge
- 2007
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Ingår i: Proc. of the ICAPS Workshop on Planning and Plan Execution for Real-World Systems, Providence, RI, 2007. ; s. 9-15
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Konferensbidrag (övrigt vetenskapligt)abstract
- To cope with the dynamics and uncertainty inherent in real world environments, autonomous mobile robots need to perform execution monitoring for verifying that their plans are executed as expected. Domain semantic knowledge has lately been proposed as a source of information to derive and monitor implicit expectations of executing actions. For instance, when the robot moves into an office, it would expect to see a desk and a chair. Such expectations are checked using the immediately available perceptual information. We propose to extend the semantic knowledge-based execution monitoring to handle situations where some of the required information is missing. To this end, we use AI sensor-based planning to actively search for such information. We show how verifying execution expectations can be formulated and solved as a planning problem involving sensing actions. Our approach is illustrated by showing test scenarios run in an indoor environment using a mobile robot.
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| 2. |
- Bouguerra, Abdelbaki, et al.
(författare)
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Handling uncertainty in semantic-knowledge based execution monitoring
- 2007
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Ingår i: IEEE/RSJ international conference on intelligent robots and systems, IROS 2007 San Diego, CA, 2007. - New York : IEEE. - 978-1-4244-0912-9 ; s. 437-443
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Konferensbidrag (refereegranskat)abstract
- Executing plans by mobile robots, in real world environments, faces the challenging issues of uncertainty and environment dynamics. Thus, execution monitoring is needed to verify that plan actions are executed as expected. Semantic domain-knowledge has lately been proposed as a source of information to derive and monitor implicit expectations of executing actions. For instance, when a robot moves into a room asserted to be an office, it would expect to see a desk and a chair. We propose to extend the semantic knowledge-based execution monitoring to take uncertainty in actions and sensing into account when verifying the expectations derived from semantic knowledge. We consider symbolic probabilistic action models, and show how semantic knowledge is used together with a probabilistic sensing model in the monitoring process of such actions. Our approach is illustrated by showing test scenarios run in an indoor environment using a mobile robot.
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| 3. |
- Bouguerra, Abdelbaki, et al.
(författare)
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Monitoring the execution of robot plans using semantic knowledge
- 2008
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Ingår i: Robotics and Autonomous Systems. - Amsterdam : North-Holland Publishing Co. - 0921-8890. ; 56:11, s. 942-954
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Tidskriftsartikel (refereegranskat)abstract
- Even the best laid plans can fail, and robot plans executed in real world domains tend to do so often. The ability of a robot to reliably monitor the execution of plans and detect failures is essential to its performance and its autonomy. In this paper, we propose a technique to increase the reliability of monitoring symbolic robot plans. We use semantic domain knowledge to derive implicit expectations of the execution of actions in the plan, and then match these expectations against observations. We present two realizations of this approach: a crisp one, which assumes deterministic actions and reliable sensing, and uses a standard knowledge representation system (LOOM); and a probabilistic one, which takes into account uncertainty in action effects, in sensing, and in world states. We perform an extensive validation of these realizations through experiments performed both in simulation and on real robots.
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| 4. |
- Bouguerra, Abdelbaki, et al.
(författare)
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Semantic knowledge-based execution monitoring for mobile robots
- 2007
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Ingår i: 2007 IEEE international conference on robotics and automation (ICRA). - 1-4244-0601-3 ; s. 3693-3698
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Konferensbidrag (refereegranskat)abstract
- We describe a novel intelligent execution monitoring approach for mobile robots acting in indoor environments such as offices and houses. Traditionally, monitoring execution in mobile robotics amounted to looking for discrepancies between the model-based predicted state of executing an action and the real world state as computed from sensing data. We propose to employ semantic knowledge as a source of information to monitor execution. The key idea is to compute implicit expectations, from semantic domain information, that can be observed at run time by the robot to make sure actions are executed correctly. We present the semantic knowledge representation formalism, and how semantic knowledge is used in monitoring. We also describe experiments run in an indoor environment using a real mobile robot
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| 5. |
- Bouguerra, Abdelbaki, et al.
(författare)
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Situation assessment for sensor-based recovery planning
- 2006
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Ingår i: 17th European Conference on Artificial Intelligence (ECAI). - IOS Press. - 1-58603-642-4 ; s. 673-677
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Konferensbidrag (refereegranskat)abstract
- We present an approach for recovery from perceptual failures, or more precisely anchoring failures. Anchoring is the problem of connecting symbols representing objects to sensor data corresponding to the same objects. The approach is based on using planning, but our focus is not on the plan generation per se. We focus on the very important aspect of situation assessment and how it is carried out for recovering from anchoring failures. The proposed approach uses background knowledge to create hypotheses about world states and handles uncertainty in terms of probabilistic belief states. This work is relevant both from the perspective of developing the anchoring framework, and as a study in plan-based recovery from epistemic failures in mobile robots. Experiments on a mobile robot are shown to validate the applicability of the proposed approach.
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| 6. |
- Broxvall, Mathias, et al.
(författare)
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Have another look on failures and recovery planning in perceptual anchoring
- 2004
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Konferensbidrag (refereegranskat)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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| 7. |
- Broxvall, Mathias, et al.
(författare)
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Recovery planning for ambiguous cases in perceptual anchoring
- 2005
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Ingår i: Proceedings of the 20th national conference on Artificial intelligence, AAAI-05 : volume 3. - 978-1-57735-236-5 ; s. 1254-1260
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Konferensbidrag (refereegranskat)abstract
- An autonomous robot using symbolic reasoning, sensing and acting in a real environment needs the ability to create and maintain the connection between symbols representing objects in the world and the corresponding perceptual representations given by its sensors. This connection has been named perceptual anchoring. In complex environments, anchoring is not always easy to establish: the situation may often be ambiguous as to which percept actually corresponds to a given symbol. In this paper, we extend perceptual anchoring to deal robustly with ambiguous situations by providing general methods for detecting them and recovering from them. We consider different kinds of ambiguous situations and present planning-based methods to recover from them. We illustrate our approach by showing experiments involving a mobile robot equipped with a color camera and an electronic nose.
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| 8. |
- Broxvall, Mathias, et al.
(författare)
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Steps toward detecting and recovering from perceptual failures
- 2004
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Ingår i: Proceedings of the 8th international conference on intelligent autonomous systems. ; s. 793-800
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Konferensbidrag (refereegranskat)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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| 9. |
- Cirillo, Marcello, et al.
(författare)
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A framework for human-aware robot planning
- 2008
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Ingår i: Tenth Scandinavian conference on artificial intelligence. - Amsterdam : IOS press. - 978-1-58603-867-0 ; s. 52-59
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Konferensbidrag (refereegranskat)abstract
- Robots that share their workspace with humans, like household or service robots, need to take into account the presence of humans when planning their actions. In this paper, we present a framework for human-aware planning in which we consider three kinds of human-robot interaction. We focus in particular on the core module of the framework, a human-aware planner that generates a sequence of actions for a robot, taking into account the status of the environment, the goals of the robot and the forecasted plan of the human. We present a first realization of this planner, together with two simple experiments that demonstrate the feasibility of our approach.
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| 10. |
- Cirillo, Marcello, et al.
(författare)
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A human-aware robot task planner
- 2009
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Ingår i: Proceedings of the 19th international conference on automated planning and scheduling, ICAPS 2009. - Menlo Park : AAAI press. - 978-1-57735-406-2 ; s. 58-65
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Konferensbidrag (refereegranskat)abstract
- The growing presence of household robots in inhabited environments arises the need for new robot task planning techniques. These techniques should take into consideration not only the actions that the robot can perform or unexpected external events, but also the actions performed by a human sharing the same environment, in order to improve the cohabitation of the two agents, e.g., by avoiding undesired situations for the human. In this paper, we present a human-aware planner able to address this problem. This planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. The planner has been tested as a standalone component and in conjunction with our framework for human-robot interaction in a real environment.
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