Robots working in unstructured environments must be capable of sensing and interpreting
their surroundings. One of the main obstacles of deep-learning-based models in the field of …

The building heights of an urban area are useful for space analysis, urban planning, and city
management. To this end, a novel method for building height calculation for an urban area is …

Domain randomisation is a very popular method for visual sim-to-real transfer in robotics,
due to its simplicity and ability to achieve transfer without any real-world images at all …

Image2mass and Pix2Vox++ are works that focus on the estimation of mass and the shape
of objects in images, respectively. Having the aid of the Pix2Vox++ in mind, the proposed …

In the maritime sector, safe vessel navigation is of great importance, particularly in
congested harbors and waterways. The focus of this work is to estimate the distance …

Large vessels such as container ships rely on experienced pilots with extensive knowledge
of the local streams and tides responsible for maneuvering the vessel to its desired location …

To enable flexible quality inspection in industrial manufacturing environments, there is an
increasing demand for easy-to-use automation systems that can aid factory workers in …

One of the biggest challenges in single-view 3D shape reconstruction in the wild is the
scarcity of< 3D shape, 2D image>-paired data from real-world environments. Inspired by …

This article presents a complete solution for autonomous mapping and inspection tasks,
namely a lightweight multi-camera drone design coupled with computationally efficient …

Domain randomization (DR) is a powerful framework that has allowed the transfer of policies
from randomized domain (aka simulation) to real robots with little to no retraining …