Simultaneous Localization and Mapping (SLAM) poses distinct challenges, especially in
settings with variable elements, which demand the integration of multiple sensors to ensure …

As the basis of mobile navigation technology, path planning has attracted the attention of the
majority of scholars. In this paper, the deep learning framework is integrated into Q-learning …

The multi-robot coverage path planning problem (MRCPP), incorporating with the sub-
problems of viewpoint sampling, viewpoint task allocation and robotic sequential planning …

The purpose is to improve the effect of substation inspection and ensure the safety of power
consumption in human society. First, this work discusses the current substation inspection …

We propose MAP-NBV, a prediction-guided active algorithm for 3D reconstruction with multi-
agent systems. Prediction-based approaches have shown great improvement in active …

Local planning is an optimization process within a mobile robot navigation stack that
searches for the best velocity vector, given the robot and environment state. Depending on …

Introduction In the field of logistics warehousing robots, collaborative operation and
coordinated control have always been challenging issues. Although deep learning and …

This paper presents a decentralized cooperative motion planning approach for surface
inspection of 3D structures which includes uncertainties like size, number, shape, position …

This study introduces a resilient and adaptive multi-robot coverage path planning approach
based on the Boustrophedon Cell Decomposition algorithm, designed to dynamically …

We present a novel coordination scheme for online multi-robot coverage with a team of
resource-constrained aerial vehicles relying on the PH-tree data structure. We propose a …