Using Artificial Potential Field Methods and Fuzzy Logic for Mobile Robot Control

Modeling and H∞ Robust Control for Mobile Robot

“…Literature [3] applied UKF arithmetic in mobile robot control and gained better control effect, but its complexity limits its practical application. Literature [4] [5] introduced intelligent arithmetic in this filed and avoided establishing the precise mathematical models, but the design of control rules are highly dependent on personal experience, and its preciseness and stability are not satisfactorily addressed and need to be further examined.…”

Path planning of humanoids based on artificial potential field method in unknown environments

“…Different modifications have been done to deal with the limitations associated with this method such as using variable charge approach (Pinto, Mendonça, Olivi, Costa, & Marcato, 2014), defining global minima (Jia & Wang, 2010), potential gradient decent algorithm (Bounini, Gingras, Pollart, & Gruyer, 2017), regression search (Li, Yamashita, Asama, & Tamura, 2012;Yang et al, 2016), terminal angle modification (Xu, Xiao, Li, & Wu, 2017), and modification of repulsion direction (Bing et al, 2011). APF approach has also been combined with other intelligent algorithms (Ahmed, Abdalla, & Abed, 2015;Bacek, Kasac, Majetic, & Brezak, 2012;Beloglazov, Finaev, Titov, Shapovalov, & Soloviev, 2016;Elkilany, Abouelsoud, & Fathelbab, 2017;Nazzal, 2017;Stoian, Ivanescu, Stoian, & Pana, 2006) as a hybridization scheme and to refine the parameters of some other algorithms. Navigational analysis of mobile robotic forms using various soft computing methods (Mohanty & Parhi, 2014;Mohanty & Parhi, 2015;Pandey & Parhi, 2016;Parhi, Deepak, Mohana, Ruppa, & Nayak, 2012;Parhi & Kundu, 2011) have been attempted by several researchers.…”