We focus on the online multi-object k-coverage problem (OMOkC), where mobile robots are
required to sense a mobile target from k diverse points of view, coordinating themselves in a …

Area coverage is an important task for mobile robots, with many real-world applications.
Motivated by potential efficiency and robustness improvements, there is growing interest in …

This paper addresses the complete area coverage problem of a known environment by
multiple-robots. Complete area coverage is the problem of moving an end-effector over all …

Motivated by potential efficiency and robustness gains, there is growing interest in the use of
multiple robots for coverage. In coverage, robots visit every point in a target area, at least …

When multiple robots are required to collaborate in order to accomplish a specific task, they
need to be coordinated in order to operate efficiently. To allow for scalability and robustness …

Centralized approaches for multi-robot coverage planning problems suffer from the lack of
scalability. Learning-based distributed algorithms provide a scalable avenue in addition to …

In this article, we explore the online multiobject k‐coverage problem in visual sensor
networks. This problem combines k‐coverage and the cooperative multirobot observation of …

We demonstrate the realization of stigmergic coverage for multi-robot systems. Compared to
current state-of-the-art algorithms for multi-robot coverage, our Stigmergy-based Coverage …

In this paper, we combine k-coverage with the Cooperative Multi-robot Observation of
Multiple Moving Targets problem, defining the new problem of online multi-object k …

Area coverage is an important task for mobile robots, with many real-world applications. In
many cases, the coverage has to be completed without the use of a map or any a priori …