According to the environment modeling approach, path planning algorithms of micro-/nanorobots are classified into searching, sampling, and dynamic aspects. The searching path planning algorithms ...

Abstract: Path planning is a critical component in UAV mission execution. While traditional optimization algorithms are mature and effective, they typically rely on expert knowledge and manual tuning, ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.

This repository implements and analytically evaluates two foundational probabilistic sample-based motion planning algorithms: RRT (Rapidly-exploring Random Tree) and its optimizing successor, RRT*.

Abstract: Unmanned aerial vehicles (UAVs) are increasingly used to search and monitor operations for various tasks. However, their operational efficiency depends on advanced path planning that can ...

In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.