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- W2388969185 abstract "A mobile robot to navigate purposefully from a start location to a target location, needs three basic requirements: sensing, learning, and reasoning. In the existing system, the mobile robot navigates in a known environment on a predefined path. However, the pervasive presence of uncertainty in sensing and learning, makes the choice of a suitable tool of reasoning and decision-making that can deal with incomplete information, vital to ensure a robust control system. This problem can be overcome by the proposed navigation method using fuzzy support vector machine (FSVM). It proposes a fuzzy logic-based support vector machine (SVM) approach to secure a collision-free path avoiding multiple dynamic obstacles. The navigator consists of an FSVM-based collision avoidance. The decisions are taken at each step for the mobile robot to attain the goal position without collision. Fuzzy-SVM rule bases are built, which require simple evaluation data rather than thousands of input-output training data. The effectiveness of the proposed method is verified by a series of simulations and implemented with a microcontroller for navigation." @default.
- W2388969185 created "2016-06-24" @default.
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- W2388969185 date "2010-01-01" @default.
- W2388969185 modified "2023-09-22" @default.
- W2388969185 title "Fuzzy Support Vector Machine-based Multi-agent Optimal Path Planning Approach to Robotics Environment." @default.
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