کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4948649 1439844 2017 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Proprioceptive shape signatures for object manipulation and recognition purposes in a robotic hand
ترجمه فارسی عنوان
امضاهای شکل ظاهری برای دستکاری و اهداف تشخیص هدف در یک دست رباتیک
کلمات کلیدی
سنجش تاکتیکی، انگشت دست دست رباتیک، تشخیص شی و دستکاری،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Tactile information has been largely exploited for object recognition with robotic hands but very few approaches have used proprioception alone. In those that do, raw values of joint angles or torques are exploited to train learning algorithms. However, these approaches under-exploit the potential of proprioception, such as its usefulness to estimate the object pose and size. Furthermore, they focus on recognizing individual objects, which increases the amount of data needed to train the algorithms. In this paper, we present an approach based only on joint angles of a robotic hand to generate a shape proprioceptive signature that is invariant to the size and position of the object. Instead of recognizing a specific object from a list, object characteristics useful for its manipulation are extracted. This signature is exploited not only for shape recognition but also for pose estimation. To illustrate the scope of this method, tests are performed on primitive shapes. Results show that the signatures are invariant within large ranges of sizes and poses. Experiments on real hand were carried, and results depicted that the method works similarly in both simulated environment and real applications. A comparison between this two results is made and discussed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Robotics and Autonomous Systems - Volume 98, December 2017, Pages 135-146
نویسندگان
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