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 …

Position estimation of wireless devices has many applications in short-range networks. Ultra-
wideband (UWB) signals provide accurate positioning capabilities that can be harnessed in …

Unmanned aerial vehicles represent a new frontier in a wide range of monitoring and
research applications. To fully leverage their potential, a key challenge is planning missions …

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

Active learning is a decision-making process. In both abstract and physical settings, active
learning demands both analysis and action. This is a review of active learning in robotics …

Graphs are a fundamental data representation that has been used extensively in various
domains. In graph-based applications, a systematic exploration of the graph such as a …

The need for efficient monitoring of spatio-temporal dynamics in large environmental
applications, such as the water quality monitoring in rivers and lakes, motivates the use of …

This paper addresses the problem of controlling mobile sensing systems to improve the
accuracy and efficiency of gathering information autonomously. It applies to scenarios such …

This paper reports a real-time monocular visual simultaneous localization and map**
(SLAM) algorithm and results for its application in the area of autonomous underwater ship …