A Predictive Human-inspired Path Planning Method Based on the Dynamic Wave Expansion Neural Network (DWENN)
Publish place: 19th Iranian conference on Biomedical Engineering
Publish Year: 1391
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICBME19_097
تاریخ نمایه سازی: 9 بهمن 1392
Abstract:
A new path planning strategy inspired by human path planning is proposed based on the dynamic wave expansion neural network (DWENN) for moving in dynamic environment. The proposed method performs in two phases. In the first phase, a coarse path is produced by using a DWENN and a cognitive map to represent the environment configuration. In the second phase, to improve the coarse path, a predictive approach is iteratively employed by combination of a locally recurrent neural network (LRNN) and a DWENN to plan a motion vector in a finite prediction horizon and executing it in a control horizon. A task is intended to evaluate the performance of the proposed method in crossing a street which includes a moving car as a dynamic obstacle. In this evaluation, different simulations with various prediction and control horizons have been performed. Our results imply that by applying a predictive method and adjusting the prediction and control horizons, DWENN can satisfactorily generate a collision-free path in dynamic environments.
Keywords:
predictive path planning , the dynamic wave expansion neural network , prediction horizon , contorl horizon
Authors
Yeganeh M Marghi
Faculty of Biomedical Engineering Amirkabir University of Technology
Bahareh Taghizadeh
Faculty of Biomedical Engineering Amirkabir University of Technology
Farzad Towhidkhah
Faculty of Biomedical Engineering Amirkabir University of Technology