Semantic segmentation enables robots to perceive and reason about their environments
beyond geometry. Most of such systems build upon deep learning approaches. As …

Autonomousrobots are often employed for data collection due to their efficiency and low
labour costs. A key task in robotic data acquisition is planning paths through an initially …

Adaptive informative path planning (AIPP) is important to many robotics applications,
enabling mobile robots to efficiently collect useful data about initially unknown …

We consider the problem of an autonomous agent equipped with multiple sensors, each
with different sensing precision and energy costs. The agent's goal is to explore the …

Abstract adaptive informative path planning (AIPP) is important to many robotics
applications, enabling mobile robots to efficiently collect useful data about initially unknown …

We consider the problem of finding an informative path through a graph, given initial and
terminal nodes and a given maximum path length. We assume that a linear noise corrupted …

Autonomous robots for gathering information on objects of interest has numerous real-world
applications because of they improve efficiency, performance and safety. Realising …

In machine learning for robotics, training data quality assumes a crucial role. Many methods
use exploration algorithms to select the most informative data points for the model, often …

This paper proposes an optimal active perception strategy using the Constructibility Gramian
(CG) as a metric to quantify the richness of the information acquired along the planned …

Adaptive informative path planning (AIPP) is important to many robotics applications,
enabling mobile robots to efficiently collect useful data about initially unknown …