Consider a large group of agents chasing a small group of moving targets. Assume each agent moves at constant speed toward the closest target. This paper studies the problem of controlling the agents indirectly by spe...
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ISBN:
(纸本)9783540767282
Consider a large group of agents chasing a small group of moving targets. Assume each agent moves at constant speed toward the closest target. This paper studies the problem of controlling the agents indirectly by specifying the motion of the targets. In particular, it considers the problem of maintaining a minimum separation distance between each pair of agents, something that is impossible to do with only one target. This paper shows that only two targets are necessary to maintain separation between four agents. It also shows results in simulation to support the conjecture that only two targets are necessary to maintain separation between any number of agents, given suitable initial conditions.
This paper investigates the use of semantic information to link ground-level occupancy maps and aerial images. A ground-level semantic map is obtained by a mobile robot equipped with an onmidirectional camera, differe...
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ISBN:
(纸本)9783540767282
This paper investigates the use of semantic information to link ground-level occupancy maps and aerial images. A ground-level semantic map is obtained by a mobile robot equipped with an onmidirectional camera, differential GPS and a laser range finder. The mobile robot uses a virtual sensor for building detection (based on omnidirectional images) to compute the ground-level semantic map, which indicates the probability of the cells being occupied by the wall of a building. These wall estimates from a ground perspective are then matched with edges detected in an aerial image. The result is used to direct a region- and boundary-based segmentation algorithm for building detection in the aerial image. This approach addresses two difficulties simultaneously: 1) the range limitation of mobile robot sensors and 2) the difficulty of detecting buildings in monocular aerial images. With the suggested method building outlines can be detected faster than the mobile robot can explore the area by itself, giving the robot an ability to "see" around corners. At the same time, the approach can compensate for the absence of elevation data in segmentation of aerial images. Our experiments demonstrate that ground-level semantic information (wall estimates) allows to focus the segmentation of the aerial image to find buildings and produce a ground-level semantic map that covers a larger area than can be built using the onboard sensors.
This paper presents preliminary results of a textureless object recognition system for an indoor mobile robot. Our approach relies on 1) segmented linear features, and 2) pairwise geometric relationships between featu...
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ISBN:
(纸本)9783540767282
This paper presents preliminary results of a textureless object recognition system for an indoor mobile robot. Our approach relies on 1) segmented linear features, and 2) pairwise geometric relationships between features. This approach is motivated by the need for recognition strategies that can handle many of indoor objects that have no little or not textural information on their surfaces, but have strong geometrical consistency within the same object class. Our matching method consists of two steps. First, we find correspondence candidates between linear fragments. Second, a spectral matching algorithm is used to find the subset of correspondences which is the most consistent. Both matching methods are learnt by using logistic classifiers. We evaluated the developed recognition system with our own database, which is composed of eight indoor object classes. We also compared the performance of our line feature based recognition approach with a SIFT feature based method. Experimentally, it turned out that the line features are superior in our problem setup - the detection of textureless objects.
Hand posture understanding is essential to human robot interaction. The existing hand detection approaches using a Viola-Jones detector have two fundamental issues, the degraded performance due to background noise in ...
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ISBN:
(纸本)9783540767282
Hand posture understanding is essential to human robot interaction. The existing hand detection approaches using a Viola-Jones detector have two fundamental issues, the degraded performance due to background noise in training images and the in-plane rotation variant detection. In this paper, a hand posture recognition system using the discrete Adaboost learning algorithm with Lowe's scale invariant feature transform (SIFI) features is proposed to tackle these issues simultaneously. In addition, we apply a sharing feature concept to increase the accuracy of multi-class hand posture recognition. The experimental results demonstrate that the proposed approach successfully recognizes three hand posture classes and can deal with the background noise issues. Our detector is in-plane rotation invariant, and achieves satisfactory multi-view hand detection.
This paper describes the software architecture of intelligent robots, developed by Center for Intelligent Robotics (CIR). The architecture employs a hybrid type consisting of deliberate, sequencing and reactive behavi...
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ISBN:
(纸本)9783540767282
This paper describes the software architecture of intelligent robots, developed by Center for Intelligent Robotics (CIR). The architecture employs a hybrid type consisting of deliberate, sequencing and reactive behaviors. The primary contributions of the architecture are the followings: 1) reusability and extensibility for the rapid development of robot systems with different requirements and 2) adaptability to distributed computing environments, different OS's and various programming languages. The architecture has successfully been applied to the development of CIR's many robot platforms such as T-Rot, Kibo and Easy Interaction Room. T-Rot and Kibo have been exhibited at the 2005 Asia-Pacific Economic Cooperation (APEC) in Korea.
This paper presents experiments in dynamic targets detection using panoramic images, which represent rich visual sources of global scenes around a robot. Moving targets (people) are distinguished as foreground pixels ...
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ISBN:
(纸本)9783540767282
This paper presents experiments in dynamic targets detection using panoramic images, which represent rich visual sources of global scenes around a robot. Moving targets (people) are distinguished as foreground pixels in binary images detected using a modified optical flow approach where the intensity of lighting source is variable. The directions of detected targets are determined using two strategies;the first one is convenient for unfolded panoramic images;it searches most probable regions in the last binary image by calculating a histogram of foreground pixels on its columns. The second approach is applied on raw panoramic images;it regroups foreground pixels using a technique that generates a new pixel's intensity depending on the intensities of its neighbors.
Research in mobile service robotics aims on development of intuitive speech interfaces for human-robot interaction. We see a service robot as a part of an intelligent environment and want to step forward discussing a ...
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ISBN:
(纸本)9783540767282
Research in mobile service robotics aims on development of intuitive speech interfaces for human-robot interaction. We see a service robot as a part of an intelligent environment and want to step forward discussing a concept where a robot does not only offer its own features via natural speech interaction but also becomes a transactive agent featuring other services' interfaces. The provided framework makes provisions for the dynamic registration of speech interfaces to allow a loosely-coupled flexible and scalable environment. An intelligent environment can evolve out of multimedia devices, home automation, communication, security, and emergency technology. These appliances offer typical wireless or stationary control interfaces. The number of different control paradigms and differently lay-outed control devices gives a certain border in usability. As speech interfaces offer a more natural way to interact intuitively with technology we propose to centralize a general speech engine on a robotic unit. This has two reasons: The acceptance to talk to a mobile unit is estimated to be higher rather than to talk to an ambient system where no communication partner is visible. Additionally the devices or functionalities to be controlled in most cases do not provide a speech interface but offer only proprietary access.
Local localization of a fully autonomous mobile robot in a partial map is an important aspect from the view point of accurate map building and safe path planning. The problem of correcting the location of a robot in a...
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ISBN:
(纸本)9783540767282
Local localization of a fully autonomous mobile robot in a partial map is an important aspect from the view point of accurate map building and safe path planning. The problem of correcting the location of a robot in a partial map worsens when sonar sensors are used. When a mobile robot is exploring the environment autonomously, it is rare to get the consistent pair of features or readings from two different positions using sonar sensors. So the approaches, which rely on readings or features matching, are prone to fail without exhaustive mathematical calculations of sonar modeling and environment modeling. This paper introduces link graph based robust two step feature chain based localization for achieving online SLAM (Simultaneous Localization And Mapping) using sonar data only. Instead of relying completely on matching of feature to feature or point to point, our approach finds possible associations between features to localize. The link graph based approach removes many false associations enhancing the SLAM process. We also map features onto Occupancy Grid (OG) framework taking advantage of its dense representation of the world. Combining features onto OG overcomes many of its limitations such as the independence assumption between cells and provides for better modeling of the sonar providing more accurate maps.
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