Omnidirectional visual odometry for a planetary rover

Position estimation for planetary rovers has been typically limited to odometry based on proprioceptive measurements such as the integration of distance traveled and measurement of heading change. Here we present and compare two methods of online visual odometry suited for planetary rovers. Both methods use omnidirectional imagery to estimate motion of the rover. One method is based on robust estimation of optical flow and subsequent integration of the flow. The second method is a full structure-from-motion solution. To make the comparison meaningful we use the same set of raw corresponding visual features for each method. The dataset is an sequence of 2000 images taken during a field experiment in the Atacama desert, for which high resolution GPS ground truth is available.

Traversability estimation for a planetary rover via experimental kernel learning in a Gaussian process framework

A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.

Motion planning and stochastic control with experimental validation on a planetary rover

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This model is used to construct a control policy for navigation to a goal region in a terrain map built using an on-board RGB-D camera. The terrain includes flat ground, small rocks, and non-traversable rocks. We report the results of 200 simulated and 35 experimental trials that validate the approach and demonstrate the value of considering control uncertainty in maintaining platform safety.

Enhanced locomotion control for a planetary rover

This article presents an approach to improve and monitor the behavior of a skid-steering rover on rough terrains. An adaptive locomotion control generates speeds references to avoid slipping situations. An enhanced odometry provides a better estimation of the distance travelled. A probabilistic classification procedure provides an evaluation of the locomotion efficiency on-line, with a detection of locomotion faults. Results obtained with a Marsokhod rover are presented throughout the paper

Virtual 3D models of insects for accelerated quarantine control

We learn from the past that invasive species have caused tremendous damage to native species and serious disruption to agricultural industries. It is crucial for us to prevent this in the future. The first step of this process is to identify correctly an invasive species from native ones. Current identification methods, relying on mainly 2D images, can result in low accuracy and be time consuming. Such methods provide little help to a quarantine officer who has time constraints to response when on duty. To deal with this problem, we propose new solutions using 3D virtual models of insects. We explain how working with insects in the 3D domain can be much better than the 2D domain. We also describe how to create true-color 3D models of insects using an image-based 3D reconstruction method. This method is ideal for quarantine control and inspection tasks that involve the verification of a physical specimen against known invasive species. Finally we show that these insect models provide valuable material for other applications such as research, education, arts and entertainment. © 2013 IEEE.

Quarantine and surveillance strategies for plant pathogen detection and control

Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.

Connected digital cities

In the future we will have a detailed ecological model of the whole planet with capabilities to explore and predict the consequences of alternative futures. However, such a planetary eco-model will take time to develop, time to populate with data, and time to validate - time the planet doesn't have. In the interim, we can model the major concentrations of energy use and pollution - our cities - and connect them to form a "talking cities network". Such a networked city model would be much quicker to build and validate. And the advantage of this approach is that it is safer and more effective for us to interfere with the operation of our cities than to tamper directly with the behaviour of natural systems. Essentially, it could be thought of as providing the planet with a nervous system and would empower us to better develop and manage sustainable cities.

Phylogenetic placement of the sugarcane orange rust pathogen Puccinia kuehnii in a historical and regional context

Sugarcane orange rust, caused by Puccinia kuehnii, was once considered a minor disease in the Australian sugar industry. However, in 2000 a new race of the pathogen devastated the high-performing sugarcane cultivar Q124, and caused the industry Aus$150–210 million in yield losses. At the time of the epidemic, very little was known about the genetic and pathogenic diversity of the fungus in Australia and neighbouring sugar industries. DNA sequence data from three rDNA regions were used to determine the genetic relationships between isolates within two P. kuehnii collections. The first collection comprised only recent Australian field isolates and limited sequence variation was detected within this population. In the second study, Australian isolates were compared with isolates from Papua New Guinea, Indonesia, China and historical herbarium collections. Greater sequence variation was detected in this collection and phylogenetic analyses grouped the isolates into three clades. All isolates from commercial cane fields clustered together including the recent Australianfield isolates and the Australian historical isolate from 1898.The other two clades included rust isolates from wild and garden canes in Indonesia and PNG. These rusts appeared morphologically similar to P. kuehnii and could potentially pose a quarantine threat to the Australian sugar industry. The results have revealed greater diversity in sugarcane rusts than previously thought.

High porosity chained aggregates from the topsoil of the lunar regolith dust

The unusual behaviour of fine lunar regolith like stickiness and low heat conductivity is dominated by the structural arrangement of its finest fraction. Here, we show the previously unknown phenomenon of a globular 3D superstructure within the dust fraction of regolith. A study using the recently developed Transmission X-ray Microscopy (TXM) with tomographic reconstruction reveals a highly porous network of cellular voids in the finest dust fraction aggregates in lunar soil. Such porous chained aggregates are composed of sub-micron particles that form a network of cellular voids a few micrometers in diameter. Discovery of such a superstructure within the finest fraction of lunar topsoil enables a model of heat transfer to be constructed.

Info-gap theory and robust design of surveillance for invasive species : the case study of Barrow Island

Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy.

Computer vision onboard UAVs for civilian tasks

Computer vision is much more than a technique to sense and recover environmental information from an UAV. It should play a main role regarding UAVs’ functionality because of the big amount of information that can be extracted, its possible uses and applications, and its natural connection to human driven tasks, taking into account that vision is our main interface to world understanding. Our current research’s focus lays on the development of techniques that allow UAVs to maneuver in spaces using visual information as their main input source. This task involves the creation of techniques that allow an UAV to maneuver towards features of interest whenever a GPS signal is not reliable or sufficient, e.g. when signal dropouts occur (which usually happens in urban areas, when flying through terrestrial urban canyons or when operating on remote planetary bodies), or when tracking or inspecting visual targets—including moving ones—without knowing their exact UMT coordinates. This paper also investigates visual serving control techniques that use velocity and position of suitable image features to compute the references for flight control. This paper aims to give a global view of the main aspects related to the research field of computer vision for UAVs, clustered in four main active research lines: visual serving and control, stereo-based visual navigation, image processing algorithms for detection and tracking, and visual SLAM. Finally, the results of applying these techniques in several applications are presented and discussed: this study will encompass power line inspection, mobile target tracking, stereo distance estimation, mapping and positioning.

High porosity chained aggregates from the topsoil of the Lunar regolith Dust

The unusual behaviour of fine lunar regolith like stickiness and low heat conductivity is dominated by the structural arrangement of its finest fraction in the outer-most topsoil layer. Here, we show the previously unknown phenomenon of building a globular 3-D superstructure within the dust fraction of the regolith. New technology, Transmission X-ray Microscopy (TXM) with tomographic reconstruction, reveals a highly porous network of cellular void system in the lunar finest dust fraction aggregates. Such porous chained aggregates are composed of sub-micron in size particles that build cellular void networks. Voids are a few micrometers in diameter. Discovery of such a superstructure within the finest fraction of the lunar topsoil allow building a model of heat transfer which is discussed.

Enhancing security and continuity management at international airports

Operators of busy contemporary airports have to balance tensions between the timely flow of passengers, flight operations, the conduct of commercial business activities and the effective application of security processes. In addition to specific onsite issues airport operators liaise with a range of organisations which set and enforce aviation-related policies and regulations as well as border security agencies responsible for customs, quarantine and immigration, in addition to first response security services. The challenging demands of coordinating and planning in such complex socio-technical contexts place considerable pressure on airport management to facilitate coordination of what are often conflicting goals and expectations among groups that have standing in respect to safe and secure air travel. What are, as yet, significantly unexplored issues in large airports are options for the optimal coordination of efforts from the range of public and private sector participants active in airport security and crisis management. A further aspect of this issue is how airport management systems operate when there is a transition from business-as-usual into an emergency/crisis situation and then, on recovery, back to ‘normal’ functioning. Business Continuity Planning (BCP), incorporating sub-plans for emergency response, continuation of output and recovery of degraded operating capacity, would fit such a context. The implementation of BCP practices in such a significant high security setting offers considerable potential benefit yet entails considerable challenges. This paper presents early results of a 4 year nationally funded industry-based research project examining the merger of Business Continuity Planning and Transport Security Planning as a means of generating capability for improved security and reliability and, ultimately, enhanced resilience in major airports. The project is part of a larger research program on the Design of Secure Airports that includes most of the gazetted ‘first response’ international airports in Australia, key Aviation industry groups and all aviation-related border and security regulators as collaborative partners. The paper examines a number of initial themes in the research, including: ? Approaches to integrating Business Continuity & Aviation Security Planning within airport operations; ? Assessment of gaps in management protocols and operational capacities for identifying and responding to crises within and across critical aviation infrastructure; ? Identification of convergent and divergent approaches to crisis management used across Austral-Asia and their alignment to planned and possible infrastructure evolution.

A generative nervous system for the planet

Generative systems are now being proposed for addressing major ecological problems. The Complex Urban Systems Project (CUSP) founded in 2008 at the Queensland University of Technology, emphasises the ecological significance of the generative global networking of urban environments. It argues that the natural planetary systems for balancing global ecology are no longer able to respond sufficiently rapidly to the ecological damage caused by humankind and by dense urban conurbations in particular as evidenced by impacts such as climate change. The proposal of this research project is to provide a high speed generative nervous system for the planet by connecting major cities globally to interact directly with natural ecosystems to engender rapid ecological response. This would be achieved by active interactions of the global urban network with the natural ecosystem in the ecological principle of entropy. The key goal is to achieve ecologically positive cities by activating self-organising cities capable of full integration into natural eco-systems and to netowork the cities globally to provide the planet with a nervous system.