کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4943136 1437621 2017 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Perceptual ambiguity maps for robot localizability with range perception
ترجمه فارسی عنوان
نقشه های ابهام ادراکی برای محلی سازی ربات با درک محدوده
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


- The main cause of the robot localization problem is perception degradation.
- Perceptual Ambiguity occurs when 1 perception fits N robot poses, for example in a corridor.
- We propose an ambiguity model for laser and sonar, independent of the robot navigation system.
- Results are colour floor maps showing “bad localization” zones, available before navigation starts.
- Our model can be applied to heterogeneous 2D or 3D range sensors platforms.
- Applications: robot localizability, design of sensory platforms, optimum robot orientation.

A mobile robot equipped with 2D or 3D range sensors can move without changing its range readings if the perceived environment is poor in features. This is an ambiguous situation because a single perception can be associated with several robot poses. In consequence, robot localization capability is reduced. The problem we address is the quantification of this perceptual ambiguity as a property inherent to the system composed of the sensor and the static environment. Perceptual ambiguity is different from uncertainty of robot localization, although it is a cause of it. We propose an ambiguity model independent of the robot navigation system. It includes a probabilistic model of the indistinguishability of range readings, a generic range sensor model that supports laser and sonar sensors, and a generic range scanner model that supports any 2D or 3D range perception platform. Ambiguity is expressed in colour floor maps, which may be available before navigation starts, and where “bad localization” zones are easily detected. Experiments with virtual and real environments perceived from 2D laser and sonar scanners are presented, including the validation of the model with a real scans dataset. Results show how ambiguous zones are precisely determined, how to determine the optimum scanner orientation and aperture, and how to reduce the number of readings per scan for improving the robot's computational load and navigation speed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 85, 1 November 2017, Pages 33-45
نویسندگان
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