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This paper presents a dead reckoning sensor system and a tracking algorithm for mobile robot localization which increases an accuracy of the estimating position at the uneven surface. A dead reckoning sensor system consists of a small, low-cost MEMS IMU and optical navigation sensor that used in laser mice. A tracking algorithm consists of multi-rate extended Kalman filter to fuse redundant and complementary...
Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise...
2D laser range finders have been widely used in mobile robot navigation. However, their use is limited to simple environments containing objects of regular geometry and shapes. Stereo vision, instead, provides 3D structural data of complex objects. In this paper, measurements from a stereo vision camera system and a 2D laser range finder are fused to dynamically plan and navigate a mobile robot in...
This paper presents a genetic algorithmic filter (GAF) approach to mobile robot simultaneous localization and mapping (SLAM). A Genetic algorithmic approach is used to solve the SLAM problem by concurrently optimizing appropriate cost functions defined over two sets of chromosome populations representing the robot pose and the environmental map. As such the methodology has the potential to produce...
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