Multi-Sensor Fusion for Localization of a Lunar Micro Rover Using Non-Vision Sensors

Autonomous navigation is a critical aspect of robotic systems, particularly in hostile and uncertain environments, and robot localization is central to navigation. Robot localization establishes its position within its surroundings. This thesis addresses the challenge of robot localization, focusing on a lunar-like environment with constraints...

Convolutional neural network framework for wind turbine electromechanical fault detection

Effective and timely health monitoring of wind turbine gearboxes and generators is essential to reduce the costs of operations and maintenance activities, especially offshore. This paper presents a scalable and lightweight convolutional neural network (CNN) framework using high-dimensional raw condition monitoring data for the automatic...

Temporal synchronization of radar and lidar streams

In multi-sensor systems, several sensors produce data streams, commonly, at different frequencies. If they are let running wild without synchronization, after a period of time, they are likely to be disordered, presenting as simultaneous measures that have been recorded at different times. That can be disastrous in many data fusion applications....

Health monitoring: a machine learning approach for anomaly detection in multi-sensor networks

Multi-sensor networks are becoming more and more popular in order to assess the post-occupancy performance of smart buildings, since they enable continuous monitoring with a high spatial resolution of the occupancy, thermal comfort and indoor air quality. An urgent, but poorly attended topic in this field is the automated detection of sensor...

A Stereovision-based Navigation System for Autonomous Vessels

Sustainability goals have reignited interest in more fuel efficient modalities for urban freight transportation. The autonomous inland vessel has the potential to enable a modality shift to the waterway, however economically-conscious solutions to the technological challenges are lacking. This paper explores the potential role of stereovision...

A Multi-Sensor Information Fusion Method Based on Factor Graph for Integrated Navigation System

The current navigation systems used in many autonomous mobile robotic applications, like unmanned vehicles, are always equipped with various sensors to get accurate navigation results. The key point is to fuse the information from different sensors efficiently. However, different sensors provide asynchronous measurements, some of which even...

Towards monitoring waterlogging with remote sensing for sustainable irrigated agriculture

Waterlogging is an increasingly important issue in irrigated agriculture that has a detri-mental impact on crop productivity. The above-ground effect of waterlogging on crops is hard to distinguish from water deficit stress with remote sensing, as responses such as stomatal closure and leaf wilting occur in both situations. Currently,...

Anomaly detection in multisensornetworks: an active learning approach: With an application to the DWA office

The built environment is becoming healthier, smarter and more energy efficient during the transition to green building activity. Multi-sensor networks are a promising component of this transition, provided that their measurements are reliable. The reliability of the data is a real concern for DWA, as they use it for control purposes as well as...

Adaptive compensation of measurement delays in multi-sensor fusion for inertial motion tracking using moving horizon estimation

Robust and accurate pose estimation of moving systems is a challenging task that is often tackled by combining information from different sensor subsystems in a multi-sensor fusion setup. To obtain robust and accurate estimates, it is crucial to respect the exact time of each measurement. Data fusion is additionally challenged when the...

Multi-Sensor Human Detection on an Intelligent Security Robot

This thesis aims to combine visual data and distance measurements from a Laser Range Finder (LRF) to recognise the presence of humans. The data from the LRF is used to find regions of interest in order to reduce the load on the visual data analysis. Deep learning convolutional neural networks have shown incredible results on visual recognition...

Hydrologic and cryospheric processes observed from space

Ten Dragon 3 projects deal with hydrologic and cryosphere processes, with a focus on the Himalayas and Qinghai – Tibet Plateau, but not limited to that. At the 1st Dragon 3 Progress Symposium in 2013 a significant potential for a better and deeper integration appeared very clearly and we worked out an overview of the ten projects identifying...

Sensors and Platforms for 3D Cadastres and 3D City Modeling: State of the Art and New Trends

Nowadays, 3D Cadastres and 3D City Modeling is done for a number of applications. The precision of the final 3D products affects the use of it. High Precision 3D data acquisition can certainly support many precision applications such as 3D registration of right, restrictions and responsibilities. The state of the Art sensors and platforms used...