The use of unmanned aerial vehicles (UAVs) to carry out remote aerial surveys has become
prominent in recent years. The UAV-based survey faces several operational issues, such as …

Coverage path planning is a major application for mobile robots, which requires robots to
move along a planned path to cover the entire map. For large-scale tasks, multirobot …

Disaster areas involving floods and earthquakes are commonly large, with the rescue time
being quite tight, suggesting multi-Unmanned Aerial Vehicles (UAV) exploration rather than …

We investigate time-optimal Multi-Robot Coverage Path Planning (MCPP) for both
unweighted and weighted terrains, which aims to minimize the coverage time, defined as the …

Coverage path planning (CPP) is the foundation of multiple robotic applications. The
efficiency of CPP is affected by the local extremum, which describes a situation with the …

With the advent and rapid growth of automation, unmanned ground vehicles (UGVs) have
emerged as a crucial technology, with applications spanning various domains, from …

The coverage path planning (CPP) algorithms play a key role in autonomous robot
applications, making area coverage operations efficient and cost-effective. The extension of …

We study graph-based Multi-Robot Coverage Path Planning (MCPP) that aims to compute
coverage paths for multiple robots to cover all vertices of a given 2D grid terrain graph G …

Multi-robot coverage planning has gained significant attention in recent years. In this letter,
we introduce a novel approach called APF-CPP (Artificial Potential Field Based Multi-Robot …

Complete coverage of multiple robots for a large map is an important collaborative planning
task, which is widely used in disaster search and rescue, forest fire prevention, resource …