کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
413127 679752 2012 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Towards hierarchical blackboard mapping on a whiskered robot
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Towards hierarchical blackboard mapping on a whiskered robot
چکیده انگلیسی

The paradigm case for robotic mapping assumes large quantities of sensory information which allow the use of relatively weak priors. In contrast, the present study considers the mapping problem for a mobile robot, CrunchBot, where only sparse, local tactile information from whisker sensors is available. To compensate for such weak likelihood information, we make use of low-level signal processing and strong hierarchical object priors. Hierarchical models were popular in classical blackboard systems but are here applied in a Bayesian setting as a mapping algorithm. The hierarchical models require reports of whisker distance to contact and of surface orientation at contact, and we demonstrate that this information can be retrieved by classifiers from strain data collected by CrunchBot’s physical whiskers. We then provide a demonstration in simulation of how this information can be used to build maps (but not yet full SLAM) in an zero-odometry-noise environment containing walls and table-like hierarchical objects.


► Mapping with only sparse, local tactile information is hard.
► We present algorithms to perform it with a whisker robot.
► Radial distance and orientation is classified from whiskers.
► We use a Bayesian blackboard and strong object priors.
► Inference is with annealed Metropolis–Hasting sampling.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Robotics and Autonomous Systems - Volume 60, Issue 11, November 2012, Pages 1356–1366
نویسندگان
, , , ,