Mobile Robot Obstacle Avoidance Based on Neural Network with a Standardization Technique
Reactive algorithm in an unknown environment is very useful to deal with dynamic obstacles that may change unexpectantly and quickly because the workspace is dynamic in real-life applications, and this work is focusing on the dynamic and unknown environment by online updating data in each step towar...
Guardado en:
Autores principales: | Karoline Kamil A. Farag, Hussein Hamdy Shehata, Hesham M. El-Batsh |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Hindawi Limited
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/5578e599ab754a36baf0053a18f02c68 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
The autonomous frontal obstacle avoidance system with trajectory updating function
por: Ryuzo HAYASHI, et al.
Publicado: (2017) -
Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
por: Mustaffa Waad Abbas, et al.
Publicado: (2013) -
Obstacles Avoidance for Mobile Robot Using Enhanced Artificial Potential Field
por: Mohamed Jasim Mohamed, et al.
Publicado: (2017) -
Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
por: Yong Dai, et al.
Publicado: (2021) -
Trajectory planning for vibration suppression and avoidance of angularly postured obstacles in a 2-D transfer system
por: Yoshiyuki NODA, et al.
Publicado: (2015)