3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-
challenged environments and serves as an essential component (ie loop-closure detection) …

The ability to interpret a scene is an important capability for a robot that is supposed to
interact with its environment. The knowledge of what is in front of the robot is, for example …

This paper addresses the problem of simultaneous 3D reconstruction and material
recognition and segmentation. Enabling robots to recognise different materials (concrete …

This paper proposes a Learning Kalman Network (LKN) based monocular visual odometry
(VO), ie LKN-VO, for on-road driving. Most existing learning-based VO focus on ego-motion …

In this paper, a novel Pixel-Voxel network is proposed for dense 3D semantic mapping,
which can perform dense 3D mapping while simultaneously recognizing and labelling the …

This paper presents a robust monocular visual teach-and-repeat (VT&R) navigation system
for long-term operation in outdoor environments. The approach leverages deep-learned …

Recognizing material categories is one of the core challenges in robotic nuclear waste
decommissioning. All nuclear waste should be sorted and segregated according to its …

This paper proposes a novel monocular teach-and-repeat navigation system with the
capability of scale awareness, ie the absolute distance between observation and goal …

This paper focuses on the influence of two important parameters of Gmapping algorithm on
the mapping accuracy. We also compute the PC consumption during mapping an indoor …

In indoor environments, the presence of people and dynamic objects is a common
occurrence. In autonomous navigation, this proposes a challenge since such objects have …