Novel idea of charging car users for using bus lanes.docx

1、Novel idea of charging car users for using bus lanesIntelligent omni-directional vision-based mobile robot fuzzy systems design and implementationExpert Systems with Applications, Volume 37, Issue 5, May 2010, Pages 4009-4019Hsuan-Ming Feng, Chih-Yung Chen, Ji-Hwei HorngClose preview| Related articl

2、es|Related reference work articles AbstractAbstract | Figures/TablesFigures/Tables | ReferencesReferences AbstractAn evolutional particle swarm optimization (PSO)-learning algorithm is proposed to automatically generate fuzzy decision rules. Due to the development of the fuzzy rule-based system, it

3、actually regulates the omni-directional vision-based mobile robot for obstacle avoidance and desired target approximation as soon as possible. In the proposed image processing algorithm, an image direct transformation method is applied to convert the omni-directional scene into panoramic normal-view

4、. Thus, the objects positions of obstacle and target are detected by the proposed color image segmentation. Human knowledge-based fuzzy systems demonstrate their well adaptability for nonlinear and time-variant features of the mobile robot to actually approach the desired location whatever it is sur

5、rounded in a known or unknown environment. In software simulations, the omni-directional mobile robot can move toward desired targets from different initial positions and various block sizes. In hardware implementations, the fuzzy control system embedded in actual mobile robot platform is used to re

6、al-time manipulate the omni-directional wheels through the motor drivers by the captured image positions of the obstacle and target. The selected fuzzy rules are efficient to control the direction and speed of omni-directional wheels to achieve the desired targets.Article Outline1. Introduction2. Ar

7、chitecture of vision-based fuzzy mobile robot system 2.1. On-line image detecting stage design2.2. Robot modeling stage design3. Mobile robot simulations and implementations 3.1. Software simulations3.2. Hardware implementation4. ConclusionsAcknowledgementsReferencesPurchase$ 39.952Kinematic paramet

8、er calibration of a car-like mobile robot to improve odometry accuracyOriginal Research ArticleMechatronics, Volume 20, Issue 5, August 2010, Pages 582-595Kooktae Lee, Woojin Chung, Kwanghyun YooClose preview| Related articles|Related reference work articles AbstractAbstract | Figures/TablesFigures/

9、Tables | ReferencesReferences AbstractOdometry provides fundamental pose estimates for wheeled vehicles. For accurate and reliable pose estimation, systematic and nonsystematic errors of odometry should be reduced. In this paper, we focus on systematic error sources of a car-like mobile robot (CLMR)

10、 and we suggest a novel calibration method. Kinematic parameters of the CLMR can be successfully calibrated by only a couple of test driving. After reducing deterministic errors by calibration, odometry accuracy can be further improved by redundant odometry fusion with the extended Kalman filter (EK

11、F). Odometry fusion reduces nonsystematic or stochastic errors. Experimental verifications are carried out using a radio-controlled miniature car.Article Outline1. Introduction2. Calibration of systematic odometry errors 2.1. Kinematics and systematic error sources of the CLMR2.2. Odometry of the CL

12、MR2.3. Test track for odometry calibration2.4. Type A error: uncalibrated tread2.5. Type B error: uncalibrated wheel diameter2.6. Systematic error calibration equation2.7. The proposed systematic error calibration scheme3. Reduction of the nonsystematic error 3.1. System model3.2. Measurement model3

13、.3. The EKF algorithm 3.3.1. Prediction stage3.3.2. Correction stage4. Simulations and experiments 4.1. Simulations4.2. Experimental systems and steering calibration4.3. Systematic error calibration results4.4. Nonsystematic error reduction result5. ConclusionAcknowledgementsReferencesPurchase$ 31.5

14、03A novel low-cost, limited-resource approach to autonomous multi-robot exploration and mappingOriginal Research ArticleRobotics and Autonomous Systems, Volume 58, Issue 2, 28 February 2010, Pages 186-202Christopher M. Gifford, Russell Webb, James Bley, Daniel Leung, Mark Calnon, Joseph Makarewicz,

15、Bryan Banz, Arvin AgahClose preview| Related articles|Related reference work articles AbstractAbstract | Figures/TablesFigures/Tables | ReferencesReferences AbstractMobile robots are becoming more heavily used in environments where human involvement is limited, impossible, or dangerous. These robots perform some of the more laborious human tasks on Earth and throughout the solar system, simultaneously saving resources and offering automation. Higher levels of autonomy are also being sought in these applications, such as distributed exploration and mapping of unknown areas.