کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
411314 679542 2014 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Kullback–Leibler divergence-based global localization for mobile robots
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Kullback–Leibler divergence-based global localization for mobile robots
چکیده انگلیسی


• Global localization module based on evolutionary computation concepts.
• The Kullback–Leibler divergence is used to generate the cost function.
• The main advantage is the ability to cope with different types of occlusions.
• Good performance with occlusions generated by uniform noise or unmodeled obstacles.

The global localization problem for mobile robots is addressed in this paper. In this field, the most common approaches solve this problem based on the minimization of a quadratic loss function or the maximization of a probability distribution. The distances obtained from the perceptive sensors are used together with the predicted ones (from the estimates in the known map) to define a cost function or a probability to optimize. In our previous work, we developed an optimization-based global localization module that used evolutionary computation concepts. In particular, the algorithm engine was the Differential Evolution method. In this work, this algorithm has been modified including the minimization of the Kullback–Leibler divergence between true observations and estimates. This divergence is used to calculate the cost function of the localization module. The algorithm has been tested in different situations and the most important improvement is the ability to cope with different types of occlusions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Robotics and Autonomous Systems - Volume 62, Issue 2, February 2014, Pages 120–130
نویسندگان
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