In the multiple fields covered by Artificial Intelligence (AI), path planning is undoubtedly one
of the issues that cover a wide range of research lines. To be able to find an optimal solution …

Sampling-based motion planning is one of the fundamental paradigms to generate robot
motions, and a cornerstone of robotics research. This comparative review provides an up-to …

Aerial robots are widely deployed, but highly cluttered environments such as dense forests
remain inaccessible to drones and even more so to swarms of drones. In these scenarios …

Swarm robotics deals with the design, construction, and deployment of large groups of
robots that coordinate and cooperatively solve a problem or perform a task. It takes …

The multi-agent pathfinding problem (MAPF) is the fundamental problem of planning paths
for multiple agents, where the key constraint is that the agents will be able to follow these …

In this article, we present an optimization-based framework for multicopter trajectory
planning subject to geometrical configuration constraints and user-defined dynamic …

Abstract Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their
goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where …

We present a distributed model predictive control (DMPC) algorithm to generate trajectories
in real-time for multiple robots. We adopted the on-demand collision avoidance method …

Abstract Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents
such that each agent reaches its goal and the agents do not collide. In recent years, variants …

The control of a multiple unmanned aerial vehicle (UAV) system is popular and attracting a
lot of attentions. This is motivated by many practical civil and commercial UAV applications …