Robot navigation in crowded public spaces is a complex task that requires addressing a
variety of engineering and human factors challenges. These challenges have motivated a …

Motion planning is a fundamental research area in robotics. Sampling-based methods offer
an efficient solution for what is otherwise a rather challenging dilemma of path planning …

In this paper, a membrane evolutionary artificial potential field (memEAPF) approach for
solving the mobile robot path planning problem is proposed, which combines membrane …

Abstract Purpose of Review Currently, there is a large body of research on multi-agent
systems addressing their different system theoretic aspects. Aerial swarms as one type of …

During the last decade, sampling-based algorithms for path planning have gained
considerable attention. The RRT*, a variant of RRT (rapidly-exploring random trees), is of …

Unmanned aerial vehicle (UAV) systems are one of the most rapidly developing, highest
level and most practical applied unmanned aerial systems. Collision avoidance and …

During the last decade, sampling-based path planning algorithms, such as probabilistic
roadmaps (PRM) and rapidly exploring random trees (RRT), have been shown to work well …

Unmanned aerial vehicle (UAV) networks are playing an important role in various areas due
to their agility and versatility, which have attracted significant attentions from both the …

Classical models of aerial swarms often describe global coordinated motion as the
combination of local interactions that happen at the individual level. Mathematically, these …

Path planning is important to the efficiency and navigation safety of USV autonomous
operation offshore. To improve path planning, this study proposes the improved ant colony …