Abstract Coverage Path Planning (CPP) is the task of determining a path that passes over all
points of an area or volume of interest while avoiding obstacles. This task is integral to many …

The small battery capacities of the mobile robot and the un-optimized planning efficiency of
the industrial robot bottlenecked the time efficiency and productivity rate of coverage tasks in …

Deep reinforcement learning has produced many success stories in recent years. Some
example fields in which these successes have taken place include mathematics, games …

Understanding atmospheric transport and dispersal events has an important role in a range
of scenarios. Of particular importance is aiding in emergency response after an intentional or …

Speed is essential in wildlife surveys due to the dynamic movement of animals throughout
their environment and potentially extreme changes in weather. In this work, we present a …

This paper deals with the path planning problem of a team of mobile robots, in order to cover
an area of interest, with prior-defined obstacles. For the single robot case, also known as …

This paper proposes a novel mission planning platform, capable of efficiently deploying a
team of UAVs to cover complex-shaped areas, in various remote sensing applications …

Patrolling involves generating patrol paths for mobile robots such that every point on the
paths is repeatedly covered. This paper focuses on patrolling in closed areas, where every …

This paper presents algorithmic solutions for the complete coverage path planning problem
using a team of mobile robots. Multiple robots decrease the time to complete the coverage …

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 …