48 citations · 146 across the 13 of their papers we have counts for
15 papers
BAMF-SLAM: Bundle Adjusted Multi-Fisheye Visual-Inertial SLAM Using Recurrent Field Transforms
Wei Zhang, Sen Wang, Xingliang Dong +2
In this paper, we present BAMF-SLAM, a novel multi-fisheye visual-inertial SLAM system that utilizes Bundle Adjustment (BA) and recurrent field transforms (RFT) to achieve accurate…
rWiFiSLAM: Effective WiFi Ranging based SLAM System in Ambient Environments
Bo Wei, Mingcen Gao, Chengwen Luo +2
In this paper, we propose rWiFiSLAM, an indoor localisation system based on WiFi ranging measurements. Indoor localisation techniques play an important role in mobile robots when t…
CURL: Continuous, Ultra-compact Representation for LiDAR
Kaicheng Zhang, Ziyang Hong, Shida Xu +1
Increasing the density of the 3D LiDAR point cloud is appealing for many applications in robotics. However, high-density LiDAR sensors are usually costly and still limited to a lev…
From market-ready ROVs to low-cost AUVs
Jonatan Scharff Willners, Ignacio Carlucho, Tomasz Łuczyński +10
Autonomous Underwater Vehicles (AUVs) are becoming increasingly important for different types of industrial applications. The generally high cost of (AUVs) restricts the access to…
Underwater inspection and intervention dataset
Tomasz Luczynski, Jonatan Scharff Willners, Elizabeth Vargas +5
This paper presents a novel dataset for the development of visual navigation and simultaneous localisation and mapping (SLAM) algorithms as well as for underwater intervention task…
Radar SLAM: A Robust SLAM System for All Weather Conditions
Ziyang Hong, Yvan Petillot, Andrew Wallace +1
A Simultaneous Localization and Mapping (SLAM) system must be robust to support long-term mobile vehicle and robot applications. However, camera and LiDAR based SLAM systems can be…
Watch and Learn: Mapping Language and Noisy Real-world Videos with Self-supervision
Yujie Zhong, Linhai Xie, Sen Wang +2
In this paper, we teach machines to understand visuals and natural language by learning the mapping between sentences and noisy video snippets without explicit annotations. Firstly…
RADIATE: A Radar Dataset for Automotive Perception in Bad Weather
Marcel Sheeny, Emanuele De Pellegrin, Saptarshi Mukherjee +3
Datasets for autonomous cars are essential for the development and benchmarking of perception systems. However, most existing datasets are captured with camera and LiDAR sensors in…
Multi-Task Reinforcement Learning based Mobile Manipulation Control for Dynamic Object Tracking and Grasping
Cong Wang, Qifeng Zhang, Qiyan Tian +6
Agile control of mobile manipulator is challenging because of the high complexity coupled by the robotic system and the unstructured working environment. Tracking and grasping a dy…
RadarSLAM: Radar based Large-Scale SLAM in All Weathers
Ziyang Hong, Yvan Petillot, Sen Wang
Numerous Simultaneous Localization and Mapping (SLAM) algorithms have been presented in last decade using different sensor modalities. However, robust SLAM in extreme weather condi…
A Comparison of Few-Shot Learning Methods for Underwater Optical and Sonar Image Classification
Mateusz Ochal, Jose Vazquez, Yvan Petillot +1
Deep convolutional neural networks generally perform well in underwater object recognition tasks on both optical and sonar images. Many such methods require hundreds, if not thousa…
300 GHz Radar Object Recognition based on Deep Neural Networks and Transfer Learning
Marcel Sheeny, Andrew Wallace, Sen Wang
For high resolution scene mapping and object recognition, optical technologies such as cameras and LiDAR are the sensors of choice. However, for robust future vehicle autonomy and…
Deep Reinforcement Learning for Autonomous Driving
Sen Wang, Daoyuan Jia, Xinshuo Weng
Reinforcement learning has steadily improved and outperform human in lots of traditional games since the resurgence of deep neural network. However, these success is not easy to be…
POL-LWIR Vehicle Detection: Convolutional Neural Networks Meet Polarised Infrared Sensors
Marcel Sheeny, Andrew Wallace, Mehryar Emambakhsh +2
For vehicle autonomy, driver assistance and situational awareness, it is necessary to operate at day and night, and in all weather conditions. In particular, long wave infrared (LW…
UnDeepVO: Monocular Visual Odometry through Unsupervised Deep Learning
Ruihao Li, Sen Wang, Zhiqiang Long +1
We propose a novel monocular visual odometry (VO) system called UnDeepVO in this paper. UnDeepVO is able to estimate the 6-DoF pose of a monocular camera and the depth of its view…