دانلود مقاله ISI انگلیسی شماره 93163
ترجمه فارسی عنوان مقاله

استراتژی انتخاب هدف مبتنی بر متا اکتیویته برای جستجوی ربات های موبایل در یک محیط ناشناخته است

عنوان انگلیسی
A meta-heuristic based goal-selection strategy for mobile robot search in an unknown environment
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
93163 2017 10 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Computers & Operations Research, Volume 84, August 2017, Pages 178-187

ترجمه کلمات کلیدی
روباتیک موبایل جستجوی روباتیک، مشکل جستجو نمودار مشکل مسافرتی تحویل، فهم،
کلمات کلیدی انگلیسی
Mobile robotics; Robotic search; Graph Search Problem; Traveling Deliveryman Problem; GRASP;
پیش نمایش مقاله
پیش نمایش مقاله  استراتژی انتخاب هدف مبتنی بر متا اکتیویته برای جستجوی ربات های موبایل در یک محیط ناشناخته است

چکیده انگلیسی

The single-robot search problem in an unknown environment is defined as the problem of finding a stationary object in the environment whose map is not known a priori. Compared to exploration, the only difference lies in goal selection as the objectives of search and exploration are dissimilar, i.e. a trajectory that is optimal in exploration does not necessarily minimize the expected value of the time to find an object along it. For this reason, in this paper we extend the preliminary ideas presented in Kulich et al. [1] to a general framework that accounts for the particular characteristics of the search problem. Within this framework, an important decision involved in the determination of the trajectory can be formulated as an instance of the Graph Search Problem (GSP), a generalization of the well-known Traveling Deliveryman Problem (TDP) which has not received much attention in the literature. We developed a tailored Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic for the GSP, which generates good quality solutions in very short computing times and is incorporated in the overall framework. The proposed approach produces very good results in a simulation environment, showing that it is feasible from a computational standpoint and the proposed strategy outperforms the standard approaches.