Motion planning of autonomous mobile robots by iterative dynamic programming

2015 ◽  
Vol 8 (3) ◽  
pp. 165-174
Author(s):  
Hee-Sang Yoon ◽  
Tae-Hyoung Park
Keyword(s):  
Dynamic Programming ◽  
Motion Planning ◽  
Mobile Robots ◽  
Autonomous Mobile Robots ◽  
Iterative Dynamic Programming

Performance analysis of fast marching-based motion planning for autonomous mobile robots in ITER scenarios

2015 ◽  
Vol 63 ◽  
pp. 36-49 ◽  
Author(s):  
Javier V. Gómez ◽  
Alberto Vale ◽  
Santiago Garrido ◽  
Luis Moreno
Keyword(s):  
Performance Analysis ◽  
Motion Planning ◽  
Mobile Robots ◽  
Autonomous Mobile Robots ◽  
Fast Marching

Mobile Sensor Motion Planning for Identification of a Contamination Source Using Iterative Dynamic Programming

2013 ◽  
Vol 198 ◽  
pp. 102-107 ◽  
Author(s):  
Paweł Ziemniak
Keyword(s):  
Dynamic Programming ◽  
Motion Planning ◽  
Information Matrix ◽  
Design Criterion ◽  
Identification Accuracy ◽  
Mobile Sensor ◽  
Contamination Source ◽  
General Scalar ◽  
Iterative Dynamic Programming ◽  
Control Forces

A systematic iterative dynamic programming procedure is proposed for on-line motion planning of mobile sensor network nodes in a specified spatial domain in such a way as to maximize the identification accuracy of an unknown contamination source. The design criterion is a general scalar measure defined on the Fisher information matrix associated with the estimated coordinates of the contamination source. The approach converts the problem to an optimal control one in which the control forces of the sensors are optimized using iterative dynamic programming.

Image-based motion planning for two mobile robots in an environment with obstacles by using cellular neural networks

2011 ◽  
Vol 2 (1) ◽  
pp. 45-50
Author(s):  
L. Ţepelea ◽  
I. Gavriluţ ◽  
A. Gacsádi ◽  
V. Tiponuţ
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Parallel Computing ◽  
Motion Planning ◽  
Mobile Robots ◽  
Cellular Neural Networks ◽  
Autonomous Mobile Robots ◽  
Planning Algorithm ◽  
Images Processing ◽  
Path Planning Algorithm

Abstract The paper presents an image-based algorithm for motion-planning of two mobile robots moving to the same target in an environment with obstacles. Due to parallel computing, the Cellular Neural Networks (CNN) techniques ensure the images processing in real-time and represent an advantageous solution for autonomous mobile robots guidance. The path planning algorithm can be improved increasing the speed of image processing, using advanced type of the CNN implementation and it can be extended for three or more robots.

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