In recent years, automatic mobile robots (AMRs) have been widely concerned in various
fields, such as material handling, unmanned aerial vehicle (UAV) cruise, automatic factories …

The proposed approach in this paper involves a new grid-based map model called “memory
grid” and a new behavior-based navigation method called “minimum risk method”. The …

In this paper, a neurofuzzy-based approach is proposed, which coordinates the sensor
information and robot motion together. A fuzzy logic system is designed with two basic …

This paper proposes a new method, minimum risk approach, to address the local path
planning to escape from local minimum during goal-oriented robot navigation in unknown …

The autonomous vehicle parking problem has drawn increased attention in recent times. It
can resolve the parking-related issues that involve minimizing human driving errors and …

Aiming at the local path planning problem of AGV, an improved artificial potential field
algorithm is proposed. Firstly, the angle function is added to the traditional algorithm to …

A new fuzzy logic algorithm is developed for mobile robot navigation in local environments.
A Pioneer robot perceives its environment through an array of eight sonar sensors and self …

This paper addresses the problem of obstacle avoidance in mobile robot navigation
systems. The navigation system is considered very important because the robot must be …

Q-learning is a classical reinforcement learning algorithm and one of the most important
methods of mobile robot path planning without a prior environmental model. Nevertheless, Q …

A hybrid control architecture combining behavior based reactive navigation and model
based environment classification has been developed. It is also hybrid in the sense that both …