Navigation of Omni-Directional Mobile Robot in Unstructured Environments using Fuzzy Logic Control

Learning Obstacle-Avoiding Lattice Paths using Swarm Heuristics: Exploring the Bijection to Ordered Trees

“…Due to one dimensional search problem and the 1-1 bijective property to ordered trees, our approach is potential to sample other combinatorial objects such as legal sequences of n pairs of parentheses, triangulated n-gons, and other combinatorial objects based on catalan numbers. In future work, we aim at studying the smoothness considerations in paths [19], [37], the integration with trajectory tracking [38], the online adaptation and integration with other intelligent schemes such as Fuzzy Logic [39], the performance for very large n and their further applications in combinatorial optimization in Robotics Fig. 11: Lower bound of the convergence of the evaluated algorithms over 20 independent runs.…”

Optimization of fuzzy rules using neural network to control mobile robot in non-structured environment

“…In spite of various suggested network topologies and learning methods, neural reactive navigators still perceive their knowledge and skills from demonstrating actions [14]. Therefore, they suffer from a very slow convergence, lack of generalization due to limited patterns to represent complicated environments, and finally information encapsulated within the network can not be interpreted into physical knowledge [15]. Consequently, the utilization of NN in reactive mobile robot navigation is limited when compared to fuzzy logic.…”