4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 -- 22 October 2020 through 24 October 2020 -- -- 165025 ; 2-s2.0-85097677344 ; Mobile robotics is a valuable tool for exploring environments inaccessible to humans due to their remoteness, cost or danger, and for performing unpleasant or laborious tasks. It is a relatively new field, until recently experimental, but it is already being applied to real problems with satisfactory results, 3D simulation plays a relevant role in both the design and control of mobile robots. It allows to reflect the situation of the real robot or simulate hypothetical scenarios. At the same time, it provides a graphical interface for robot control, in this paper, we present a scheme for guiding a robot into an uncharted area by using the fuzzy c-means segmentation algorithm and k-NN classification to classify the safe and unsafe areas, our method proves to be fast with satisfactory results in terms of both segmentation, classification, and correct path planning. © 2020 IEEE.
Robot pathplanning by image segmentation using the fuzzy C-means algoritm and KNN algorithm
2020-01-01
Conference paper
Electronic Resource
English
Classification , Path Planning , Segmentation , FCM , Fuzzy , KNN , Robot
DDC: | 629 |
Algoritm optimalʹnogo proektirovanija letatelʹnogo apparata
TIBKAT | 1970
|Algoritm rascheta optimalnojj struktury remontnogo cikla lokomotivov
IuD Bahn | 1994
|IPCC ALGORITM: MOBILE DETECTION IN 3D-LIDAR AND CAMERA DATA
British Library Conference Proceedings | 2013
|