This paper describes a probabilistic online map merging system for a single mobile robot. It performs intermittent exploration by fusing laser scan matching and omnidirectional vision. Moreover, it can also be adapted...
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This paper describes a probabilistic online map merging system for a single mobile robot. It performs intermittent exploration by fusing laser scan matching and omnidirectional vision. Moreover, it can also be adapted to a multi-robot system for large scale environments. Map merging is achieved by means of a probabilistic Haar-based place recognition system using omnidirectional images and is capable of discriminating new and previously visited locations in the current or previously collected maps. This dramatically reduces the search space for laser scan matching. The combination of laser range finding and omnidirectional vision is very attractive because they reinforce one another when there is sufficient structure and visual information in the environment. In other cases, they complement one another, leading to improved robustness of the system. This is the first system to combine a probabilistic Haar-based place recognition system using omnidirectional images with laser range finding to merge maps. The proposed system is also algorithmically simple, efficient and does not require any offline processing. Experimental results of the approach clearly illustrate that the proposed system can perform both online map merging and exploration robustly using a single robot configuration in a real indoor lab environment.
In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor use...
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Current approaches to determine the orientation and maintain balance of mobile robots typically rely on gyro and tilt sensor data. This paper presents an image-based sensor fusion approach using sensed data from a MEM...
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Current approaches to determine the orientation and maintain balance of mobile robots typically rely on gyro and tilt sensor data. This paper presents an image-based sensor fusion approach using sensed data from a MEMS gyro and a digital image processing system. The approach relies on the statistical property of man-made or cultural environments to exhibit predominately more horizontal and vertical edges than oblique edges. The gyro data and statistical image data is Kalman filtered to estimate the roll angle. The system was tested both indoors and outdoors at the University of Arizona campus, and it demonstrated continuous roll angle drift correction, without prior knowledge of or training on the environment. The algorithm was then implemented in a biped walking robot to demonstrate the real-time, end-to-end proof of concept.
We are extremely pleased to present this special issue of the Journal of Control Theory and *** dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adap...
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We are extremely pleased to present this special issue of the Journal of Control Theory and *** dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over *** optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.
A high frequency transformer is a critical component in a dual active bridge converter (DAB) used in a power electronics-based solid state transformer. Operation of a DAB converter requires its transformer to have a s...
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This research exploits the fact embedded in immune system to communicate between innate immune response and adaptive immune response levels. We first sort infeasible antibodies based on their constraint violation valu...
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This research exploits the fact embedded in immune system to communicate between innate immune response and adaptive immune response levels. We first sort infeasible antibodies based on their constraint violation values and feasible antibodies based on their objective function values. The next processes assesses in what directions individuals with high affinities should move to improve their objective function values and reduce constraint violations. This information is used to estimate the mutation direction to infeasible antibodies. This approach is validated and tested using benchmark functions used in related researches and the results obtained are compared with studies made in similar area. The performance acquired is competitive and in some cases even better than those of state-of-the-art. The algorithm is also designed to obtain feasible solutions in every run executed.
To realize real-time goal-oriented navigation for a mobile robot in unpredictable environments, a fuzzy reactive system is proposed in this paper. Besides the establishment of the fuzzy logic system, this paper focuse...
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To realize real-time goal-oriented navigation for a mobile robot in unpredictable environments, a fuzzy reactive system is proposed in this paper. Besides the establishment of the fuzzy logic system, this paper focuses on the the physical meaning of the parameters in the fuzzy system, and proposes a systematic method to automatically suppress redundant fuzzy rules from the rule base. Under the control of the proposed system with automatic redundant fuzzy rule removal, the mobile robot can preferably avoid obstacles autonomously, and generate reasonable trajectories toward the target in various situations. The effectiveness and efficiency of the proposed approach are demonstrated by simulation and experimental studies.
A method based on textural features and Adaboost for detecting buildings in satellite images is proposed. Several local textural features including mean and standard deviation of image intensity and gradient, Zernike ...
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A method based on textural features and Adaboost for detecting buildings in satellite images is proposed. Several local textural features including mean and standard deviation of image intensity and gradient, Zernike moments, Circular-Mellin features, Haralick features, Fourier Power Spectrum, Wavelets, Gabor Filters, and a set features extracted from HSV color space are extracted. Adaboost learning algorithm is employed for both classification and determining the beneficial feature subset, due to its feature selector nature. Some operation including morphological operators are applied for post processing. The approach was tested on a set of satellite images having different types of buildings and promising experimental results are achieved.
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