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This paper describes a Takagi-Sugeno (T-S) fuzzy model adopted solution to the simultaneous localization and mapping (SLAM) problem with two-sensor data association (TSDA) method. Fuzzy Kalman filtering of the SLAM problem (FKF-SLAM) is used in this paper together with newly proposed data association algorithm. An extended TSDA (ETSDA) method is introduced for the SLAM problem in mobile robot navigation...
This paper describes an improved solution to the simultaneous localization and mapping (SLAM) problem based on pseudolinear models. Accurate estimation of vehicle and landmark states is one of the key issues for successful mobile robot navigation if the configuration of the environment and initial robot location are unknown. A state estimator which can be designed to use the nonlinearity as it is...
This paper presents an alternative solution to simultaneous localization and mapping (SLAM) problem by applying a fuzzy Kalman filter using a pseudolinear measurement model of nonholonomic mobile robots. Takagi-Sugeno fuzzy model based on observation for nonlinear system is adopted to represent the process and measurement models of the vehicle-landmarks system. The complete system of the vehicle-landmarks...
This paper proposes a fuzzy logic based solution to the SLAM problem. Less error prone vehicle process model is proposed to improve the accuracy and the faster convergence of state estimation. Evolution of vehicle motion is modeled using dead-reckoned odometry measurements as control inputs. Nonlinear process model and observation model are formulated as pseudolinear models and approximated by local...
This paper describes an improved solution to mobile robot localization and map building problem based on pseudolinear measurement model through bias reduction approach. Accurate estimation of vehicle and landmark states is one of the key issues for successful mobile robot navigation if the configuration of the environment and initial robot location are unknown. Direct linearization of nonlinear models...
This paper deals with the implementation of emotions to generate intelligent behavior among the cooperative and job distributed mobile robots performing a specified task and to develop an easier form of communication. A human emotion model is adapted to multirobot system to achieve their well organized tasks. With the emotional capability, each robot can distinguish the changed environment and can...
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