جابهجایی اجسام توسط یک سیستم چندرباتی توزیعشده با استفاده از یک معماری ترکیبی
محورهای موضوعی : مهندسی برق و کامپیوترطاهر حکمت فر 1 , الیپس مسیحی 2
1 - دانشگاه تربیت مدرس
2 - دانشگاه تربیت مدرس
کلید واژه: برنامه ریزی مسیر جابهجایی همکارانه اجسام سیستم های چندرباتی هماهنگی همکاری,
چکیده مقاله :
مقاله پیش رو بر روی حل همکارانه مسأله جابهجایی اجسام توسط سیستمهای چندرباتی توزیعشده تمرکز دارد. دو چالش مهم برنامهریزی مسیر و همکاری رباتها باعث دشوارشدن این مسأله شده است. در این مسأله رباتها باید با خودداری از موانع و با بهرهگیری از یک مکانیزم هماهنگی و همکاری مناسب، جسم را از مسیر عاری از تصادم به نقطه هدف برسانند. رویکرد ارائهشده در این مقاله متشکل از یک ساختار دولایه است که از مزایای هر دو معماری متمرکز و غیر متمرکز بهره میبرد. لایه سراسری با آگاهی کامل از اجزای محیط امکان رسیدن به جواب بهینه را با استفاده از الگوریتم جدید ORT فراهم میکند. لایه محلی نیز با انجام محلی برخی از پردازشها باعث کاهش آسیبپذیری، بار پردازشی سیستم مرکزی و هزینه کلی سیستم میشود. هماهنگی مورد نیاز بین رباتها در این لایه به کمک ارتباط رادیویی برقرار میشود و برای برنامهریزی مسیر حرکت محلی رباتها از ترکیب الگوریتمهای میدان پتانسیل و Tangent Bug استفاده شده است. رویکرد پیشنهادی بر روی یک سیستم چندرباتی متشکل از رباتهای KUKA youBot و با استفاده از شبیهساز Webots پیادهسازی شده است. به منظور بررسی کارایی رویکرد پیشنهادی، نتایج حاصل از آزمایشات مختلف با الگوریتم ORT و همچنین الگوریتم RRT به دست آمده و مقایسه گردید. این نتایج نشانگر کارایی مناسب رویکرد پیشنهادی است.
This paper addresses the cooperative object transportation by a multi robot distributed system, which is a difficult problem due to path planning and robot cooperation challenges. In this problem, a number of robots should transport an object to a goal point safely while avoiding obstacles and utilizing a proper coordination and cooperation mechanism. The proposed method has a two-layer structure which benefits from both centralized and decentralized architectures. The global level takes advantage of full knowledge of environment to plan an optimal path using the new Optimally-Connect Random Tree (ORT) method, and the local level performs some local processes to reduce the system’s overall processing load and cost and increase its robustness. The required coordination between the robots is realized via radio communication, and for local path planning of the robots a combination of potential fields and TangentBug algorithms has been used. The proposed method has been implemented on multiple KUKA youBot mobile manipulators in the Webots simulation software, and its performance has been evaluated through various experimentations and the results of implementing and comparing the ORT and Rapidly-exploring Random Trees (RRT) showed the advantage of the proposed method.
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