Particle Swarm Optimisation as a Hardware-Oriented Meta-heuristic for Image Analysis
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Evaluation of parallel particle swarm optimization algorithms within the CUDATM architecture
Information Sciences: an International Journal
Hardware opposition-based PSO applied to mobile robot controllers
Engineering Applications of Artificial Intelligence
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In this paper we propose a simplified, hardware-oriented algorithm for object detection, based on Particle Swarm Optimization. Starting from an algorithm coded in a high-level language which has shown to perform well, both interms of accuracy and of computation efficiency, the simplified version can be implemented on an FPGA. After describing the original algorithm, we describe how it has been simplified for hardware implementation. We show how the intrinsic modularity of the algorithm permits to define a general core, independent of the specific application, which implements object search, along with a simple application specific-module, which implements a problem-dependent fitness function. This makes the system easily reconfigurable when switching between different object detection applications. Finally, we show some examples of application of our algorithm and discuss about possible future developments.