Deep Raman spectroscopy for the non-invasive standoff detection of concealed chemical threat agents

Deep Raman spectroscopy has been utilized for the standoff detection of concealed chemical threat agents from a distance of 15 meters under real life background illumination conditions. By using combined time and space resolved measurements, various explosive precursors hidden in opaque plastic containers were identified non-invasively. Our results confirm that combined time and space resolved Raman spectroscopy leads to higher selectivity towards the sub-layer over the surface layer as well as enhanced rejection of fluorescence from the container surface when compared to standoff spatially offset Raman spectroscopy. Raman spectra that have minimal interference from the packaging material and good signal-to-noise ratio were acquired within 5 seconds of measurement time. A new combined time and space resolved Raman spectrometer has been designed with nanosecond laser excitation and gated detection, making it of lower cost and complexity than picosecond-based laboratory systems.

CAT-SLAM : probabilistic localisation and mapping using a continuous appearance-based trajectory

This paper describes a new system, dubbed Continuous Appearance-based Trajectory Simultaneous Localisation and Mapping (CAT-SLAM), which augments sequential appearance-based place recognition with local metric pose filtering to improve the frequency and reliability of appearance-based loop closure. As in other approaches to appearance-based mapping, loop closure is performed without calculating global feature geometry or performing 3D map construction. Loop-closure filtering uses a probabilistic distribution of possible loop closures along the robot’s previous trajectory, which is represented by a linked list of previously visited locations linked by odometric information. Sequential appearance-based place recognition and local metric pose filtering are evaluated simultaneously using a Rao–Blackwellised particle filter, which weights particles based on appearance matching over sequential frames and the similarity of robot motion along the trajectory. The particle filter explicitly models both the likelihood of revisiting previous locations and exploring new locations. A modified resampling scheme counters particle deprivation and allows loop-closure updates to be performed in constant time for a given environment. We compare the performance of CAT-SLAM with FAB-MAP (a state-of-the-art appearance-only SLAM algorithm) using multiple real-world datasets, demonstrating an increase in the number of correct loop closures detected by CAT-SLAM.

Wind-energy based path planning for electric unmanned aerial vehicles using Markov Decision Processes

Exploiting wind-energy is one possible way to ex- tend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

Reducing Actuator Switchings for Motion Control of Autonomous Underwater Vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle. Indeed, due to the vehicles' design and the actuation modes usually under consideration for underwater plateforms the number of actuator switchings must be kept to a small value to insure feasibility and precision. This is the main objective of the algorithm presented in this paper. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six-degrees-of freedom and one is minimally actuated with control motions in the vertical plane only.

Controlling Minimally-Actuated Vehicles for Applications in Ocean Observation

Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.

Do anti-inflammatory agents promote linear ablation lesion discontinuities? : an electrophysiological examination

Background: Catheter ablation for atrial fibrillation (AF) is more efficacious than antiarrhythmic therapy. Post ablation recurrences reduce ablation effectiveness and are contributed by lesion discontinuity in the fibrotic linear ablation lesions. The anti-fibrotic role of statins in reducing AF is being assessed in current trials. By reducing the chronic pathological fibrosis that occurs in AF they may reduce AF. However if statins also have an effect on the acute therapeutic fibrosis of an ablation, this could exacerbate lesion discontinuity and AF recurrence. We tested the hypothesis that statins attenuate ablation lesion continuity in a recognised pig atrial linear ablation model. Aims: To assess whether Atorvastatin diminishes the bi-directional conduction block produced by a linear atrial ablation lesion. Methods: Sixteen pigs were randomised to statin (n=8) or placebo (n=8) with drug pre-treatment for 3 days and a further 4 weeks. At initial electrophysiological study (EPS1) 3D right atrium (RA) mapping and a vertical ablation linear lesion in the posterior RA with bidirectional conduction block were completed (Gepstein Circ 1999). Follow-up electrophysiological assessment (EPS2) at 28 days assessed bidirectional conduction block maintenance. Results: Data of 15/16 (statin=7) pigs were analysed. Mean lesion length was 3.7 ± 0.8cm with a mean of 17.9 ± 5.7 lesion applications. Bi-directional conduction block was confirmed in 15/15 pigs (100%) at EPS1 and EPS2. Conclusions: Atorvastatin did not affect ablation lesion continuity in this pig atrial linear ablation model. If patients are on long-term statins for AF reduction, periablation cessation is probably not necessary.

Outdoor sensornet design and deployment : experiences from a sugar farm

A wireless sensor network collected real-time water-quality measurements to investigate how current irrigation practices—in particular, underground water salination—affect the environment. New protocols provided high end-to-end packet delivery rates in the hostile deployment environment.

OpenFABMAP : an open source toolbox for appearance-based loop closure detection

Appearance-based loop closure techniques, which leverage the high information content of visual images and can be used independently of pose, are now widely used in robotic applications. The current state-of-the-art in the field is Fast Appearance-Based Mapping (FAB-MAP) having been demonstrated in several seminal robotic mapping experiments. In this paper, we describe OpenFABMAP, a fully open source implementation of the original FAB-MAP algorithm. Beyond the benefits of full user access to the source code, OpenFABMAP provides a number of configurable options including rapid codebook training and interest point feature tuning. We demonstrate the performance of OpenFABMAP on a number of published datasets and demonstrate the advantages of quick algorithm customisation. We present results from OpenFABMAP’s application in a highly varied range of robotics research scenarios.

Proteasome inhibitors as anti-cancer agents

The ubiquitin (Ub)-proteasome pathway is the major nonlysosomal pathway of proteolysis in human cells and accounts for the degradation of most short-lived, misfolded or damaged proteins. This pathway is important in the regulation of a number of key biological regulatory mechanisms. Proteins are usually targeted for proteasome-mediated degradation by polyubiquitinylation, the covalent addition of multiple units of the 76 amino acid protein Ub, which are ligated to 1-amino groups of lysine residues in the substrate. Polyubiquitinylated proteins are degraded by the 26S proteasome, a large, ATP-dependent multicatalytic protease complex, which also regenerates monomeric Ub. The targets of this pathway include key regulators of cell proliferation and cell death. An alternative form of the proteasome, termed the immunoproteasome, also has important functions in the generation of peptides for presentation by MHC class I molecules. In recent years there has been a great deal of interest in the possibility that proteasome inhibitors, through elevation of the levels of proteasome targets, might prove useful as a novel class of anti-cancer drugs. Here we review the progress made to date in this area and highlight the potential advantages and weaknesses of this approach.

Does section 420A impose ‘strict liability’ upon controllers for acts or omissions of agents and experts?

This article addresses in depth the question of whether section 420A of the Corporations Act 2001 (Cth) imposes ‘strict liability’ upon a controller for the failure of an agent or expert to take reasonable care. The weight of existing authority appears to suggest that controllers are liable under s 420A for the carelessness of their agents or expert advisers. However, a closer analysis of the text of the provision and relevant Australian and UK case law demonstrates that this aspect of the statutory construction of s 420A remains very much an open question. This article ultimately contends for a construction of s 420A which requires a controller to adequately supervise and scrutinise, but which does not render a blameless controller strictly liable for all careless acts and omissions of agents and expert advisers.

Control and application of minimally-actuated underwater vehicles

Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats. With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.

Extending persistent monitoring by combining ocean models and Markov decision processes

Ocean processes are complex and have high variability in both time and space. Thus, ocean scientists must collect data over long time periods to obtain a synoptic view of ocean processes and resolve their spatiotemporal variability. One way to perform these persistent observations is to utilise an autonomous vehicle that can remain on deployment for long time periods. However, such vehicles are generally underactuated and slow moving. A challenge for persistent monitoring with these vehicles is dealing with currents while executing a prescribed path or mission. Here we present a path planning method for persistent monitoring that exploits ocean currents to increase navigational accuracy and reduce energy consumption.

Visible and near infrared spectroscopy of Hayabusa re-entry using semi-autonomous tracking

A ground-based tracking camera and co-aligned slit-less spectrograph were used to measure the spectral signature of visible radiation emitted from the Hayabusa capsule as it entered into the Earth's atmosphere in June 2010. Good quality spectra were obtained that showed the presence of radiation from the heat shield of the vehicle and the shock-heated air in front of the vehicle. An analysis of the black body nature of the radiation concluded that the peak average temperature of the surface was about (3100±100) K.

Beyond here-and-now : extending shared physical experiences to shared conceptual experiences

For robots to use language effectively, they need to refer to combinations of existing concepts, as well as concepts that have been directly experienced. In this paper, we introduce the term generative grounding to refer to the establishment of shared meaning for concepts referred to using relational terms. We investigated a spatial domain, which is both experienced and constructed using mobile robots with cognitive maps. The robots, called Lingodroids, established lexicons for locations, distances, and directions through structured conversations called where-are-we, how-far, what-direction, and where-is-there conversations. Distributed concept construction methods were used to create flexible concepts, based on a data structure called a distributed lexicon table. The lexicon was extended from words for locations, termed toponyms, to words for the relational terms of distances and directions. New toponyms were then learned using these relational operators. Effective grounding was tested by using the new toponyms as targets for go-to games, in which the robots independently navigated to named locations. The studies demonstrate how meanings can be extended from grounding in shared physical experiences to grounding in constructed cognitive experiences, giving the robots a language that refers to their direct experiences, and to constructed worlds that are beyond the here-and-now.

Visual route recognition with a handful of bits

In this paper we use a sequence-based visual localization algorithm to reveal surprising answers to the question, how much visual information is actually needed to conduct effective navigation? The algorithm actively searches for the best local image matches within a sliding window of short route segments or 'sub-routes', and matches sub-routes by searching for coherent sequences of local image matches. In contract to many existing techniques, the technique requires no pre-training or camera parameter calibration. We compare the algorithm's performance to the state-of-the-art FAB-MAP 2.0 algorithm on a 70 km benchmark dataset. Performance matches or exceeds the state of the art feature-based localization technique using images as small as 4 pixels, fields of view reduced by a factor of 250, and pixel bit depths reduced to 2 bits. We present further results demonstrating the system localizing in an office environment with near 100% precision using two 7 bit Lego light sensors, as well as using 16 and 32 pixel images from a motorbike race and a mountain rally car stage. By demonstrating how little image information is required to achieve localization along a route, we hope to stimulate future 'low fidelity' approaches to visual navigation that complement probabilistic feature-based techniques.