In order to effectively improve the path‐finding capability of a multirobot system in a
decentralized control approach, a dynamic motion planning model based on graph neural …

Multi-robot systems are widely used in spatially distributed tasks, and their collaborative path
planning is of great significance for working efficiency. Currently, different multi-robot …

Multi-agent path planning is an important re-search direction in robotics due to its wide
range of applications such as autonomous driving, automatic storage and so on. Off-the …

This letter presents a data-driven decentralized trajectory optimization approach for multi-
robot motion planning in dynamic environments. When navigating in a shared space, each …

Multirobot path planning in complex environments is a challenging research area. This
article proposes a path planning method for multirobot systems based on distributed …

Effective communication is key to successful, decentralized, multi-robot path planning. Yet, it
is far from obvious what information is crucial to the task at hand, and how and when it must …

This paper proposes reinforcement learning methods to perform an object transportation
task for multiple robots. This task consists of two main subtasks, path planning and motion …

Multirobot path planning leads multiple robots from start positions to designated goal
positions by generating efficient and collision-free paths. Multirobot systems realize …

Multi-robot navigation is a challenging task, especially for many robots, since individual
gains may more often than not adversely affect the global gain. This paper investigates the …

This paper focuses on achieving efficient and safe navigation for robots in dynamic and
unpredictable environments. We propose a hierarchical path planning framework that …