Speedup of interval type 2 fuzzy logic systems based on GPU for robot navigation

Authors:
Long Thanh Ngo;Dzung Dinh Nguyen;Long The Pham;Cuong Manh Luong
Affiliations:
Department of Information Systems, Le Quy Don Technical University, Hanoi, Vietnam;Department of Information Systems, Le Quy Don Technical University, Hanoi, Vietnam;Department of Information Systems, Le Quy Don Technical University, Hanoi, Vietnam;Department of Information Systems, Le Quy Don Technical University, Hanoi, Vietnam
Venue:
Advances in Fuzzy Systems - Special issue on High Performance Fuzzy Systems for Real World Problems
Year:
2012

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Abstract

As the number of rules and sample rate for type 2 fuzzy logic systems (T2FLSs) increases, the speed of calculations becomes a problem. The T2FLS has a large membership value of inherent algorithmic parallelism that modern CPU architectures do not exploit. In the T2FLS, many rules and algorithms can be speedup on a graphics processing unit (GPU) as long as the majority of computation a various stages and components are not dependent on each other. This paper demonstrates how to install interval type 2 fuzzy logic systems (IT2-FLSs) on the GPU and experiments for obstacle avoidance behavior of robot navigation. GPU-based calculations are high-performance solution and free up the CPU. The experimental results show that the performance of the GPU is many times faster than CPU.