کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
711671 892134 2008 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Direct Policy Search Reinforcement Learning for Autonomous Underwater Cable Tracking
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
Direct Policy Search Reinforcement Learning for Autonomous Underwater Cable Tracking
چکیده انگلیسی

This paper proposes a field application of a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot in a cable tracking task. The learning system is characterized by using a Direct Policy Search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEUAUV.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC Proceedings Volumes - Volume 41, Issue 1, 2008, Pages 155-160