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

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.

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.

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.

Astronomy on the high seas

This article describes the development and launching of a stargazing activity on two cruise ships, Pacific Dawn and Pacific Sun, which sail from Australian ports. The session included a presentation entitled “Voyage to the Stars” that gave passengers an overview of the life cycle of stars from star-birth nebulae to white dwarfs and black holes. In the presentation it was noted that ancient mariners used the celestial sphere to navigate. The presentation was followed by on-deck observing sessions in which objects shown in the presentation were viewed with the naked eye, binoculars and a small telescope. The activity seemed to be well received and resulted in numerous questions to the presenter of the activity. Many people said that the activity had kindled or rekindled their interest in astronomy.

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.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Editors' introduction

In approaching this Special Issue on Foresight, Innovation and Entrepreneurship (FI&E) we considered that globalisation and rapid modernisation were increasingly creating the need for social reflexivity. We thought that in respect to the production and diffusion of innovations, both social and technical, that the landscape for new enterprise was characterised by widening change horizons and deeper ethical concerns. As a consequence of the greater demand for innovation to achieve economic prosperity, it was conceived that 'unforesightful' innovation may have irreparable affects on social and ecological systems and uncertain implications for our futures. Therefore, we considered a new intellectual alliance between FI&E was potentially a matter of human survival. New approaches to thinking about how and what we innovate, the choices we face for new enterprise creation and the influence of infrastructure for generating entrepreneurship, we considered, would need to emerge if we are to positively impact human and planetary sustainability in the 21st century. Hence this special issue was designed to bring together cross-disciplinary research aimed at exploring the synergies between foresight, innovation and entrepreneurship and the way in which these connections may be taking place in both the practical and theoretical sense.

Significant Dot: The 1769 transit of Venus - a tale of astronomy, medicine and empire

This article places the 6 June 2012 transit of Venus in the context of James Cook’s voyage from England to the South Pacific to observe the 1769 transit of Venus. A description is given on how to use a computer program called Stellarium to ‘observe’ the 1769 transit of Venus exactly as Cook saw it from the island of Tahiti in the South Pacific.