Active simultaneous localization and map** (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …

Simultaneous localization and map** responds to the problem of building a map of the
environment without any prior information and based on the data obtained from one or more …

Exploration and collision-free navigation through an unknown environment is a fundamental
task for autonomous robots. In this paper, a novel exploration strategy for Micro Aerial …

Can artificial intelligence (AI) be more ethical than human intelligence? Can it respect
human values better than a human? This article examines some issues raised by the AI with …

Autonomous mobile devices operating in confined environments, such as pipes,
underground tunnel systems, and cave networks, face multiple open challenges from the …

This work presents a fully integrated tree-based combined exploration-planning algorithm:
exploration-rapidly-exploring random trees (RRT)(ERRT). The algorithm is focused on …

Bathymetric simultaneous localization and map** (SLAM) methods have shown their
potential in deep-sea navigation and map** for autonomous underwater vehicles (AUVs) …

Abstract Purpose of Review Multi-robot exploration—ie, the problem of map** unknown
features of an environment—is fundamental in many tasks, including search and rescue …

Robot exploration in GPS-denied environments is a significant challenge due to the lack of
reliable localization strategies. In this article, we propose a dual-layer planning approach …

This paper introduces FALCON, a novel F ast A utonomous exp L oration framework using
CO verage path guida N ce, which aims at setting a new performance benchmark in the field …