Experimental evaluation of an autonomous surface vehicle for water quality and greenhouse gas emission monitoring

This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

An autonomous surface vehicle for water quality monitoring

This paper describes a novel Autonomous Surface Vehicle capable of navigating throughout complex inland water storages and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran can collect this information throughout the water column whilst the vehicle is moving. A unique feature of this ASV is its integration into a storage scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper provides an overview of the vehicle design and operation including control, laser-based obstacle avoidance, and vision-based inspection capabilities. Experimental results are shown illustrating its ability to continuously collect key water quality parameters and compliment intensive manual monitoring campaigns.

Vision-based docking using an autonomous surface vehicle

This paper describes the development of a novel vision-based autonomous surface vehicle with the purpose of performing coordinated docking manoeuvres with a target, such as an autonomous underwater vehicle, at the water's surface. The system architecture integrates two small processor units; the first performs vehicle control and implements a virtual force based docking strategy, with the second performing vision-based target segmentation and tracking. Furthermore, the architecture utilises wireless sensor network technology allowing the vehicle to be observed by, and even integrated within an ad-hoc sensor network. Simulated and experimental results are presented demonstrating the autonomous vision- based docking strategy on a proof-of-concept vehicle.

Nanowire sensor response to reactive gas environment

The response of an originally developed catalytic sensor with a Nb2 O5 nanowire array at its outer surface to the varying density of O atoms is experimentally and numerically studied. This technique can be used to measure one order of magnitude lower densities of O atoms and achieve a stable linear response in a significantly broader pressure range compared to conventional catalytic probes with a flat surface. The nanostructured outer surface also acts as a thermal barrier against sensor overheating. This approach is generic and can be used for reactive species detection in other reactive gas environments.

Catalytic probes with nanostructured surface for gas/discharge diagnostics : a study of a probe signal behaviour

Catalytic probes are used for plasma diagnostics in order to quantify the density of neutral atoms. The probe response primarily depends on the probe material and its surface morphology. Here we report on the design, operation and modelling of the response of niobium pentoxide sensors with a flat and nanowire (NW) surfaces. These sensors were used to detect neutral oxygen atoms in the afterglow region of an inductively coupled rf discharge in oxygen. A very different response of the flat-surface and NW probes to the varying densities of oxygen atoms was explained by modelling heat conduction and taking into account the associated temperature gradients. It was found that the nanostructure probe can measure in a broader range than the flat oxide probe due to an increase in the surface to volume ratio, and the presence of nanostructures which act as a thermal barrier against sensor overheating. These results can be used for the development of the new generation of catalytic probes for gas/discharge diagnostics in a range of industrial and environmental applications.

An acoustically enhanced gold film Raman sensor on a lithium niobate substrate

The surface enhanced Raman scattering effect has shown immense potential for detecting trace amounts of explosive vapor molecules. To date, efforts to produce a commercially available, reliable SERS sensor have been impeded by an inability to separate the electromagnetic enhancement produced by the metallic nanostructure from other signal enhancing effects. Here, we show a new Raman sensor that uses surface acoustic waves (SAWs) to produce controllable surface structures on gold films deposited on LiNbO3 substrates that modulate the Raman signal of a target compound (thiophenol) adsorbed on the films. We demonstrate that this sensor can dynamically control the Raman signal simply by changing the SAW’s amplitude, allowing the Raman signal enhancement factor to be directly measured with no variation in the concentration of the target compound. The physically adsorbed molecules can be removed from the sensor without physical cleaning or damage, making it possible to reuse it for real-time Raman detection.

Modeling kinect sensor noise for improved 3D reconstruction and tracking

We contribute an empirically derived noise model for the Kinect sensor. We systematically measure both lateral and axial noise distributions, as a function of both distance and angle of the Kinect to an observed surface. The derived noise model can be used to filter Kinect depth maps for a variety of applications. Our second contribution applies our derived noise model to the KinectFusion system to extend filtering, volumetric fusion, and pose estimation within the pipeline. Qualitative results show our method allows reconstruction of finer details and the ability to reconstruct smaller objects and thinner surfaces. Quantitative results also show our method improves pose estimation accuracy. © 2012 IEEE.

Towards coordinated vision-based docking using an Autonomous Surface Vehicle

This paper describes the development and experimental evaluation of a novel vision-based Autonomous Surface Vehicle with the purpose of performing coordinated docking manoeuvres with a target, such as an Autonomous Underwater Vehicle, on the water’s surface. The system architecture integrates two small processor units; the first performs vehicle control and implements a virtual force obstacle avoidance and docking strategy, with the second performing vision-based target segmentation and tracking. Furthermore, the architecture utilises wireless sensor network technology allowing the vehicle to be observed by, and even integrated within an ad-hoc sensor network. The system performance is demonstrated through real-world experiments.

DS-VBF : dual sink vector-based routing protocol for underwater wireless sensor network

Underwater wireless sensor networks (UWSNs) have become the seat of researchers' attention recently due to their proficiency to explore underwater areas and design different applications for marine discovery and oceanic surveillance. One of the main objectives of each deployed underwater network is discovering the optimized path over sensor nodes to transmit the monitored data to onshore station. The process of transmitting data consumes energy of each node, while energy is limited in UWSNs. So energy efficiency is a challenge in underwater wireless sensor network. Dual sinks vector based forwarding (DS-VBF) takes both residual energy and location information into consideration as priority factors to discover an optimized routing path to save energy in underwater networks. The modified routing protocol employs dual sinks on the water surface which improves network lifetime. According to deployment of dual sinks, packet delivery ratio and the average end to end delay are enhanced. Based on our simulation results in comparison with VBF, average end to end delay reduced more than 80%, remaining energy increased 10%, and the increment of packet reception ratio was about 70%.

Predicting the speed of a Wave Glider autonomous surface vehicle from wave model data

A key component of robotic path planning is ensuring that one can reliably navigate a vehicle to a desired location. In addition, when the features of interest are dynamic and move with oceanic currents, vehicle speed plays an important role in the planning exercise to ensure that vehicles are in the right place at the right time. Aquatic robot design is moving towards utilizing the environment for propulsion rather than traditional motors and propellers. These new vehicles are able to realize significantly increased endurance, however the mission planning problem, in turn, becomes more difficult as the vehicle velocity is not directly controllable. In this paper, we examine Gaussian process models applied to existing wave model data to predict the behavior, i.e., velocity, of a Wave Glider Autonomous Surface Vehicle. Using training data from an on-board sensor and forecasting with the WAVEWATCH III model, our probabilistic regression models created an effective method for forecasting WG velocity.