| 1. |
- Andreasson, Henrik, 1977-, et al.
(författare)
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Has something changed here? : Autonomous difference detection for security patrol robots
- 2007
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Ingår i: 2007 IEEE/RSJ international conference on intelligent robots and systems. - New York, NY, USA : IEEE. - 9781424409129 ; , s. 3429-3435
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Konferensbidrag (refereegranskat)abstract
- This paper presents a system for autonomous change detection with a security patrol robot. In an initial step a reference model of the environment is created and changes are then detected with respect to the reference model as differences in coloured 3D point clouds, which are obtained from a 3D laser range scanner and a CCD camera. The suggested approach introduces several novel aspects, including a registration method that utilizes local visual features to determine point correspondences (thus essentially working without an initial pose estimate) and the 3D-NDT representation with adaptive cell size to efficiently represent both the spatial and colour aspects of the reference model. Apart from a detailed description of the individual parts of the difference detection system, a qualitative experimental evaluation in an indoor lab environment is presented, which demonstrates that the suggested system is able register and detect changes in spatial 3D data and also to detect changes that occur in colour space and are not observable using range values only.
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| 2. |
- Bordignon, Mirko, et al.
(författare)
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Seamless integration of robots and tiny embedded devices in a PEIS-ecology
- 2007
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Ingår i: IEEE/RSJ international conference on intelligent robots and systems, IROS 2007. - New York : IEEE. - 9781424409129 ; , s. 3101-3106
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Konferensbidrag (refereegranskat)abstract
- The fields of autonomous robotics and ambient intelligence are converging toward the vision of smart robotic environments, in which tasks are performed via the cooperation of many networked robotic devices. To enable this vision, we need a common communication and cooperation model that can be shared between robotic devices at different scales, ranging from standard mobile robots to tiny embedded devices. Unfortunately, today's robot middlewares are too heavy to run on tiny devices, and middlewares for embedded devices are too simple to support the cooperation models needed by an autonomous smart environment. In this paper, we propose a middleware model which allows the seamless integration of standard robots and simple off-the-shelf embedded devices. Our middleware is suitable for building truly ubiquitous robotics applications, in which devices of very different scales and capabilities can cooperate in a uniform way. We discuss the principles and implementation of our middleware, and show an experiment in which a mobile robot, a commercial mote, and a custom-built mote cooperate in a home service scenario.
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| 3. |
- 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. - 9781424409129 ; , 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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| 4. |
- Cielniak, Grzegorz, 1975-, et al.
(författare)
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Improved data association and occlusion handling for vision-based people tracking by mobile robots
- 2007
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Ingår i: 2007 IEEE/RSJ international conference on intelligent robots and systems. - New York, NY, USA : IEEE. - 9781424409129 ; , s. 3436-3441
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Konferensbidrag (refereegranskat)abstract
- This paper presents an approach for tracking multiple persons using a combination of colour and thermal vision sensors on a mobile robot. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is then incorporated into the tracker.
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| 5. |
- Dornhege, Christian, et al.
(författare)
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Behavior Maps for Online Planning of Obstacle Negotiation and Climbing on Rough Terrain
- 2007
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Ingår i: In <em>Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)</em>. - : IEEE conference proceedings. - 9781424409129 ; , s. 3005-3011
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Konferensbidrag (refereegranskat)abstract
- To autonomously navigate on rough terrain is a challenging problem for mobile robots, requiring the ability to decide whether parts of the environment can be traversed or have to be bypassed, which is commonly known as Obstacle Negotiation (ON). In this paper, we introduce a planning framework that extends ON to the general case, where different types of terrain classes directly map to specific robot skills, such as climbing stairs and ramps. This extension is based on a new concept called behavior maps, which is utilized for the planning and execution of complex skills. Behavior maps are directly generated from elevation maps, i.e. two-dimensional grids storing in each cell the corresponding height of the terrain surface, and a set of skill descriptions. Results from extensive experiments are presented, showing that the method enables the robot to explore successfully rough terrain in real-time, while selecting the optimal trajectory in terms of costs for navigation and skill execution.
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| 6. |
- Dornhege, Christian, et al.
(författare)
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Fully Autonomous Planning and Obstacle Negotiation on Rough Terrain Using Behavior Maps
- 2007
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Ingår i: In <em>Video Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)</em>. - 9781424409129 ; , s. 2561-2562
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Konferensbidrag (refereegranskat)abstract
- To autonomously navigate on rough terrain is a challenging problem for mobile robots, requiring the ability to decide whether parts of the environment can be traversed or have to be bypassed, which is commonly known as Obstacle Negotiation (ON). In this paper, we introduce a planning framework that extends ON to the general case, where different types of terrain classes directly map to specific robot skills, such as climbing stairs and ramps. This extension is based on a new concept called behavior maps, which is utilized for the planning and execution of complex skills. Behavior maps are directly generated from elevation maps, i.e. two-dimensional grids storing in each cell the corresponding height of the terrain surface, and a set of skill descriptions. Results from extensive experiments are presented, showing that the method enables the robot to explore successfully rough terrain in real-time, while selecting the optimal trajectory in terms of costs for navigation and skill execution.
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| 7. |
- Folkesson, John, 1960-, et al.
(författare)
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Feature tracking for underwater navigation using sonar
- 2007
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Ingår i: Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems San Diego, CA, USA, Oct 29 - Nov 2, 2007. - : IEEE conference proceedings. - 9781424409129 ; , s. 3678-3684
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Konferensbidrag (refereegranskat)abstract
- Tracking sonar features in real time on an underwater robot is a challenging task. One reason is the low observability of the sonar in some directions. For example, using a blazed array sonar one observes range and the angle to the array axis with fair precision. The angle around the axis is poorly constrained. This situation is problematic for tracking features in world frame Cartesian coordinates as the error surfaces will not be ellipsoids. Thus Gaussian tracking of the features will not work properly. The situation is similar to the problem of tracking features in camera images. There the unconstrained direction is depth and its errors are highly non-Gaussian. We propose a solution to the sonar problem that is analogous to the successful inverse depth feature parameterization for vision tracking, introduced by [1]. We parameterize the features by the robot pose where it was first seen and the range/bearing from that pose. Thus the 3D features have 9 parameters that specify their world coordinates. We use a nonlinear transformation on the poorly observed bearing angle to give a more accurate Gaussian approximation to the uncertainty. These features are tracked in a SLAM framework until there is enough information to initialize world frame Cartesian coordinates for them. The more compact representation can then be used for a global SLAM or localization purposes. We present results for a system running real time underwater SLAM/localization. These results show that the parameterization leads to greater consistency in the feature location estimates.
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| 8. |
- Freidovich, Leonid B, et al.
(författare)
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Experimental implementation of stable oscillations of the Furuta pendulum around the upward equilibrium
- 2007
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Ingår i: IEEE/RSJ International conference on intelligent robots and systems, 2007. IROS 2007. - Piscataway, N.J : IEEE Operations Center. - 9781424409129 ; , s. 171-176
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Konferensbidrag (refereegranskat)abstract
- Recently, a new technique for generating periodic motions in mechanical systems which have less actuators than degrees of freedom has been proposed. A motivating example for studying such motions is a dynamically stabilized walking robot, where the target trajectory is periodic, and one of the joints - the ankle joint - is unactuated, or weakly actuated. In this paper, the technique is implemented on the Furuta pendulum, an experimental testbed that is simpler than a walking robot but retains many of the key challenges - it is underactuated, open-loop unstable, and practical problems such as friction and velocity estimation must be overcome. We present a detailed description of the practical implementation of the controller. The experiments show that the technique is sufficiently robust to be useful in practice.
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| 9. |
- Kleiner, Alexander, et al.
(författare)
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Decentralized SLAM for Pedestrians without direct Communication
- 2007
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Ingår i: In <em>Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)</em>. - : IEEE conference proceedings. - 9781424409129 ; , s. 1461-1466
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Konferensbidrag (refereegranskat)abstract
- We consider the problem of Decentralized Simultaneous Localization And Mapping (DSLAM) for pedestrians in the context of Urban Search And Rescue (USAR). In this context, DSLAM is a challenging task. First, data exchange fails due to cut off communication links. Second, loop-closure is cumbersome due to the fact that fireman will intentionally try to avoid performing loops, when facing the reality of emergency response, e.g. while they are searching for victims. In this paper, we introduce a solution to this problem based on the non-selfish sharing of information between pedestrians for loop-closure. We introduce a novel DSLAM method which is based on data exchange and association via RFID technology, not requiring any radio communication. The approach has been evaluated within both outdoor and semi-indoor environments. The presented results show that sharing information between single pedestrians allows to optimize globally their individual paths, even if they are not able to communicate directly.
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| 10. |
- Kleiner, Alexander, et al.
(författare)
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Genetic MRF Model Optimization for Real-Time Victim Detection in Search and Rescue
- 2007
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Ingår i: <em>IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS)</em>. - : IEEE conference proceedings. - 9781424409129 ; , s. 3025-3030
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Konferensbidrag (refereegranskat)abstract
- One primary goal in rescue robotics is to deploy a team of robots for coordinated victim search after a disaster. This requires robots to perform subtasks, such as victim detection, in real-time. Human detection by computationally cheap techniques, such as color thresholding, turn out to produce a large number of false-positives. Markov Random Fields (MRFs) can be utilized to combine the local evidence of multiple weak classifiers in order to improve the detection rate. However, inference in MRFs is computational expensive. In this paper we present a novel approach for the genetic optimizing of the building process of MRF models. The genetic algorithm determines offline relevant neighborhood relations with respect to the data, which are then utilized for generating efficient MRF models from video streams during runtime. Experimental results clearly show that compared to a Support Vector Machine (SVM) based classifier, the optimized MRF models significantly reduce the false-positive rate. Furthermore, the optimized models turned out to be up to five times faster then the non-optimized ones at nearly the same detection rate.
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