Mobile robotics research is an emerging area since last three decades. The present
research on mobile robotics addresses the problems which are mainly on path planning …

With the rapid development of autonomous driving technology, collision avoidance has
become a research hotspot since it has the potential to increase safety. To obtain a collision …

The development of techniques for autonomous navigation in real-world environments
constitutes one of the major trends in the current research on robotics. An important problem …

Autonomous robots operating in uncertain or hazardous environments subject to state safety
constraints must be able to identify and isolate faulty components in a time-optimal manner …

Social robots have evolved in diverse applications with the emergence of deep
reinforcement learning methods. However, safe and secure navigation of social robots in a …

In this paper, dynamic collision-free trajectory generation in a nonstationary environment is
studied using biologically inspired neural network approaches. The proposed neural …

The research presented in this paper approaches the issue of navigation using an
automated guided vehicle (AGV) in industrial environments. The work describes the …

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 …

This paper presents a modified pulse-coupled neural network (MPCNN) model for real-time
collision-free path planning of mobile robots in nonstationary environments. The proposed …

Abstract Artificial Potential Filed (APF) is the most well-known method that is used in mobile
robot path planning, however, the shortcoming is that the local minima. To overcome this …