Active simultaneous localization and mapping (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 mapping 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 …

This work presents a modular and hierarchical approach to learn policies for exploring 3D
environments, calledActive Neural SLAM'. Our approach leverages the strengths of both …

We propose a dual-resolution scheme to achieve time-efficient autonomous exploration with
one or many robots. The scheme maintains a high-resolution local map of the robot's …

Simultaneous localization and mapping (SLAM) consists in the concurrent construction of a
model of the environment (the map), and the estimation of the state of the robot moving …

Exploration is an important aspect of robotics, whether it is for mapping, rescue missions, or
path planning in an unknown environment. Frontier Exploration planning (FEP) and …

Mapping is a crucial task in robotics and a fundamental building block of most mobile
systems deployed in the real world. Robots use different environment representations …

Now in its third edition, this textbook is a comprehensive introduction to the multidisciplinary
field of mobile robotics, which lies at the intersection of artificial intelligence, computational …

Formative feedback has long been recognised as an effective tool for student learning, and
researchers have investigated the subject for decades. However, the actual implementation …

This paper presents a novel path planning algorithm for autonomous, uncertainty-aware
exploration and mapping of unknown environments using aerial robots. The proposed …