4 accepted papers
Successful path planning for Unmanned Aerial Vehicles (UAVs) in challenging environments with narrow openings, such as disaster areas, requires attitude to be considered. State-of-the-art methods incorporate attitude only in the refinement stage. We introduce a first-of-a-kind global minimum cost pa
The availability of real-time semantics greatly improves the core geometric functionality of SLAM systems, enabling numerous robotic and AR/VR applications. We present a new methodology for real-time semantic mapping from RGB-D sequences that combines a 2D neural network and a 3D network based on a
Active stereo systems are used in many robotic applications that require 3D information. These depth sensors, however, suffer from stereo artefacts and do not provide dense depth estimates. In this work, we present the first self-supervised depth completion method for active stereo systems that pred
With the aim of bridging the gap between high quality reconstruction and robot motion planning, we propose an efficient system that leverages the concept of adaptive-resolution volumetric mapping, which naturally integrates with the hierarchical decomposition of space in an octree data structure. In