A modular hybrid SLAM for the 3D mapping of large scale environments

Underground mining environments pose many unique challenges to the task of creating extensive, survey quality 3D maps. The extreme characteristics of such environments require a modular mapping solution which has no dependency on Global Positioning Systems (GPS), physical odometry, a priori information or motion model simplification. These restrictions rule out many existing 3D mapping approaches. This work examines a hybrid approach to mapping, fusing omnidirectional vision and 3D range data to produce an automatically registered, accurate and dense 3D map. A series of discrete 3D laser scans are registered through a combination of vision based bearing-only localization and scan matching with the Iterative Closest Point (ICP) algorithm. Depth information provided by the laser scans is used to correctly scale the bearing-only feature map, which in turn supplies an initial pose estimate for a registration algorithm to build the 3D map and correct localization drift. The resulting extensive maps require no external instrumentation or a priori information. Preliminary testing demonstrated the ability of the hybrid system to produce a highly accurate 3D map of an extensive indoor space

Vision Based Localization under Dynamic Illumination

Localization in dynamically illuminated environments is often difficult due to static objects casting dynamic shadows. Feature extraction algorithms may detect both the objects and their shadows, producing conflict in localization algorithms. This work examines a colour model that separates brightness from chromaticity and applies it to eliminate features caused by dynamic illumination. The colour model is applied in two novel ways. Firstly, the chromaticity distortion of a single feature is used to determine if the feature is the result of illumination alone i.e. a shadow. Secondly, the chromaticity distortion of features matched between images is examined to determine if the monochrome based algorithm has matched them correctly. These two applications are put through a variety of tests in simulated then real world environments to assess their effectiveness in dynamically illuminated scenarios. The results demonstrate a significant reduction in the number of feature mismatches between images with dynamic light sources. The evaluation of the techniques individually in a Simultaneous Localization and Mapping (SLAM) task show substantial improvements in accuracy, with the combination of the two techniques producing a localization result that is highly robust to the environmental lighting

“CATAStrophy,” a Genome-Informed Trophic Classification of Filamentous Plant Pathogens – How Many Different Types of Filamentous Plant Pathogens Are There?

The traditional classification of fungal and oomycete phytopathogens into three classes – biotrophs, hemibiotrophs, or necrotrophs – is unsustainable. This study highlights multiple phytopathogen species for which these labels have been inappropriately applied. We propose a novel and reproducible classification based solely on genome-derived analysis of carbohydrate-active enzyme (CAZyme) gene content called CAZyme-Assisted Training And Sorting of -trophy (CATAStrophy). CATAStrophy defines four major divisions for species associated with living plants. These are monomertrophs (Mo) (corresponding to biotrophs), polymertrophs (P) (corresponding to necrotrophs), mesotrophs (Me) (corresponding to hemibiotrophs), and vasculartrophs (including species commonly described as wilts, rots, or anthracnoses). The Mo class encompasses symbiont, haustorial, and non-haustorial species. Me are divided into the subclasses intracellular and extracellular Me, and the P into broad and narrow host sub-classes. This gives a total of seven discrete plant-pathogenic classes. The classification provides insight into the properties of these species and offers a facile route to develop control measures for newly recognized diseases. Software for CATAStrophy is available online at https://github.com/ccdmb/catastrophy. We present the CATAStrophy method for the prediction of trophic phenotypes based on CAZyme gene content, as a complementary method to the traditional tripartite “biotroph–hemibiotroph–necrotroph” classifications that may encourage renewed investigation and revision within the fungal biology community.</p

Binar Space Program: Binar-1 Results and Lessons Learned

The Binar Space Program is a recently formed space research and education group part of the Space Science and Technology Center at Curtin University in Western Australia. Recently launching the first CubeSat from the state, Binar-1, the team is making steps towards creating a sustainable mission schedule for research and education. The Binar-1 mission primary objective was to demonstrate the custom designed systems made by PhD students and engineers at the university. The main technology being demonstrated was the integrated Binar CubeSat Core, which compacted the Electrical Power System, Attitude Determination and Control System, and flight computer system into 0.25U. Alongside this, the team also aimed to learn about end-to-end spacecraft mission design and engage with the public to build an understanding of the importance of space industry and research in the country. Binar-1 was deployed from the International Space Station on the 6th of October 2021, and initially was silent for 15 days until the Binar team was able to make contact by enabling a secondary beacon. This paper will present the Binar-1 mission including the custom design, operations, failure analysis, and results before finally summarizing the lessons learned by the team while flying Western Australia’s first space capability

Binar Space Program: Mission Two Payloads and Operations Plan

The second mission of Western Australia’s Binar Space Program consists of three 1U CubeSats targeting a 2023 launch. Aiming to improve the platform for future missions, the primary purpose of Binar 2, 3 and 4 is on-orbit testing of radiation shielding alloys developed by CSIRO. In this first-of-its-kind experiment, all three simultaneously deployed Binar spacecraft will contain radiation sensing payloads to assess the efficacy of various compositions of Australian made radiation shielding alloys. Alongside this, hardware changes to the Binar platform are discussed, including deployable solar arrays, additional communications solutions, and a removable payload bay. The Iridium network will be leveraged to test its suitability for CubeSat targeted re-entry. Several software-based payloads are implemented, including on-board hardware emulation, enabling an industry partner to control the spacecraft in a demonstration of remote operations capability. An undergraduate student lead project will continue on from Binar-1 to see a star tracker flown for testing alternative methods of attitude determination. From a community perspective, strengthening the engagement between amateur radio operators and the Binar Space Program will be explored by expanding on what amateurs can do with on-orbit satellites. Lastly, autonomous agile mission planning will be tested through an on-board multipurpose simulation running on the dual-core flight computer