System Identification of multi-rotor UAVs using echo state networks

Controller design for aircraft with unusual configurations presents unique challenges, particularly in extracting valid mathematical models of the MRUAVs behaviour. System Identification is a collection of techniques for extracting an accurate mathematical model of a dynamic system from experimental input-output data. This can entail parameter identification only (known as grey-box modelling) or more generally full parameter/structural identification of the nonlinear mapping (known as black-box). In this paper we propose a new method for black-box identification of the non-linear dynamic model of a small MRUAV using Echo State Networks (ESN), a novel approach to train Recurrent Neural Networks (RNN)

Strategy Synthesis for Autonomous Agents Using PRISM

We present probabilistic models for autonomous agent search and retrieve missions derived from Simulink models for an Unmanned Aerial Vehicle (UAV) and show how probabilistic model checking and the probabilistic model checker PRISM can be used for optimal controller generation. We introduce a sequence of scenarios relevant to UAVs and other autonomous agents such as underwater and ground vehicles. For each scenario we demonstrate how it can be modelled using the PRISM language, give model checking statistics and present the synthesised optimal controllers. We conclude with a discussion of the limitations when using probabilistic model checking and PRISM in this context and what steps can be taken to overcome them. In addition, we consider how the controllers can be returned to the UAV and adapted for use on larger search areas

Comparison of nonlinear dynamic inversion and inverse simulation

No abstract available

A Comparison of Inverse Simulation-Based Fault Detection in a Simple Robotic Rover with a Traditional Model-Based Method

Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing \textit{input} residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances

Inverse Simulation as a Tool for Fault Detection and Isolation in Planetary Rovers

With manned expeditions to planetary bodies beyond our own and the Moon currently intractable, the onus falls upon robotic systems to explore and analyse extraterrestrial environments such as Mars. These systems typically take the form of wheeled rovers, designed to navigate the difficult terrain of other worlds. Rovers have been used in this role since Lunokhod 1 landed on the Moon in 1970. While early rovers were remote controlled, communication latency with bodies beyond the Moon and the desire to improve mission effectiveness have resulted in increasing autonomy in planetary rovers. With an increase in autonomy, however, comes an increase in complexity. This can have a negative impact on the reliability of the rover system. With a fault-free system an unlikely prospect and human assistance millions of miles away, the rover must have a robust fault detection, isolation and recovery (FDIR) system. The need for comprehensive FDIR is demonstrated by the recent Chinese lunar rover, Yutu (or “Jade Rabbit”). Yutu was rendered immobile 42 days after landing and remained so for the duration of its operational life: 31 months. While its lifespan far exceeded its expected value, Yutu's inability to move severely impaired its ability to perform its mission. This clearly highlights the need for robust FDIR. A common approach to FDIR is through the generation and analysis of residuals. Output residuals may be obtained by comparing the outputs of the system with predictions of those outputs, obtained from a mathematical model of the system which is supplied with the system inputs. Output residuals allow simple detection and isolation of faults at the output of the system. Faults in earlier stages of the system, however, propagate through the system dynamics and can disperse amongst several of the outputs. This problem is exemplified by faults at the input, which can potentially excite every system state and thus manifest in every output residual. Methods exist for decoupling and analysing output residuals such that input faults may be isolated, however, these methods are complex and require comprehensive development and testing. A conceptually simpler approach is presented in this paper. Inverse simulation (InvSim) is a numerical method by which the inputs of a system are obtained for a desired output. It does so by using a Newton-Raphson algorithm to solve a non-linear model of the system for the input. When supplied with the outputs of a fault-afflicted system, InvSim produces the input required to drive a fault-free system to this output. The fault therefore manifests itself in this generated input signal. The InvSim-generated input may then be compared to the true system input to generate input residuals. Just as a fault at an output manifests itself in the residual for that output alone, a fault at an input similarly manifests itself only in the residual for that input. InvSim may also be used to generate residuals at other locations in the system, by considering distinct subsystems with their own inputs and outputs. This ability is tested comprehensively in this paper. Faults are applied to a simulated rover at a variety of locations within the system structure and residuals generated using both InvSim and conventional forward simulation. Residuals generated using InvSim are shown to facilitate detection and isolation of faults in several locations using simple analyses. By contrast, forward simulation requires the use of complex analytical methods such as structured residuals or adaptive thresholds

Kaon Photoproduction and the Λ\Lambda Decay Parameter α−\alpha_-

The weak decay parameter $\alpha_-$ of the $\Lambda$ is an important quantity for the extraction of polarization observables in various experiments. Moreover, in combination with $\alpha_+$ from $\bar\Lambda$ decay it provides a measure for matter-antimatter asymmetry. The weak decay parameter also affects the decay parameters of the $\Xi$ and $\Omega$ baryons and, in general, any quantity in which the polarization of the $\Lambda$ is relevant. The recently reported value by the BESIII collaboration of $0.750(9)(4)$ is significantly larger than the previous PDG value of $0.642(13)$ that had been accepted and used for over 40 years. In this work we make an independent estimate of $\alpha_-$, using an extensive set of polarization data measured in kaon photoproduction in the baryon resonance region and constraints set by spin algebra. The obtained value is 0.721(6)(5). The result is corroborated by multiple statistical tests as well as a modern phenomenological model, showing that our new value yields the best description of the data in question. Our analysis supports the new BESIII finding that $\alpha_-$ is significantly larger than the previous PDG value. Any experimental quantity relying on the value of $\alpha_-$ should therefore be re-considered.Comment: 6 pages, 1 figure

Creating a Safety Assurance Case for an ML Satellite-Based Wildfire Detection and Alert System

Wildfires are a common problem in many areas of the world with often catastrophic consequences. A number of systems have been created to provide early warnings of wildfires, including those that use satellite data to detect fires. The increased availability of small satellites, such as CubeSats, allows the wildfire detection response time to be reduced by deploying constellations of multiple satellites over regions of interest. By using machine learned components on-board the satellites, constraints which limit the amount of data that can be processed and sent back to ground stations can be overcome. There are hazards associated with wildfire alert systems, such as failing to detect the presence of a wildfire, or detecting a wildfire in the incorrect location. It is therefore necessary to be able to create a safety assurance case for the wildfire alert ML component that demonstrates it is sufficiently safe for use. This paper describes in detail how a safety assurance case for an ML wildfire alert system is created. This represents the first fully developed safety case for an ML component containing explicit argument and evidence as to the safety of the machine learning

Investigations in multi-resolution modelling of the quadrotor micro air vehicle

Multi-resolution modelling differs from standard modelling in that it employs multiple abstractions of a system rather than just one. In describing the system at several degrees of resolution, it is possible to cover a broad range of system behaviours with variable precision. Typically, model resolution is chosen by the modeller, however the choice of resolution for a given objective is not always intuitive. A multi-resolution model provides the ability to select optimal resolution for a given objective. This has benefits in a number of engineering disciplines, particularly in autonomous systems engineering, where the behaviours and interactions of autonomous agents are of interest. To investigate both the potential benefits of multi-resolution modelling in an autonomous systems context and the effect of resolution on systems engineering objectives, a multi-resolution model family of the quadrotor micro air vehicle is developed. The model family is then employed in two case studies. First, non-linear dynamic inversion controllers are derived from a selection of the models in the model family, allowing the impact of resolution on a model-centric control strategy to be investigated. The second case study employs the model family in the optimisation of trajectories in a wireless power transmission. This allows both study of resolution impact in a multi-agent scenario and provides insight into the concept of laser-based wireless power transmission. In addition to the two primary case studies, models of the quadrotor are provided through derivation from first principles, system identification experiments and the results of a literature survey. A separate model of the quadrotor is employed in a state estimation experiment with low-fidelity sensors, permitting further discussion of both resolution impact and the benefits of multi-resolution modelling. The results of both the case studies and the remainder of the investigations highlight the primary benefit of multi-resolution modelling: striking the optimal balance between validity and efficiency in simulation. Resolution is demonstrated to have a non-negligible impact on the outcomes of both case studies. Finally, some insights in the design of a wireless power transmission are provided from the results of the second case study

Autonomous agent behaviour modelled in PRISM -- a case study

This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/N508792/1].Formal verification of agents representing robot behaviour is a growing area due to the demand that autonomous systems have to be proven safe. In this paper we present an abstract definition of autonomy which can be used to model autonomous scenarios and propose the use of small-scale simulation models representing abstract actions to infer quantitative data. To demonstrate the applicability of the approach we build and verify a model of an unmanned aerial vehicle (UAV) in an exemplary autonomous scenario, utilising this approach.Publisher PD

Marine sedimentary records of chemical weathering evolution in the western Himalaya since 17 Ma

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zhou, P., Ireland, T., Murray, R. W., & Clift, P. D. Marine sedimentary records of chemical weathering evolution in the western Himalaya since 17 Ma. Geosphere, 17(3), (2021): 824–853, https://doi.org/10.1130/GES02211.1.The Indus Fan derives sediment from the western Himalaya and Karakoram. Sediment from International Ocean Discovery Program drill sites in the eastern part of the fan coupled with data from an industrial well near the river mouth allow the weathering history of the region since ca. 16 Ma to be reconstructed. Clay minerals, bulk sediment geochemistry, and magnetic susceptibility were used to constrain degrees of chemical alteration. Diffuse reflectance spectroscopy was used to measure the abundance of moisture-sensitive minerals hematite and goethite. Indus Fan sediment is more weathered than Bengal Fan material, probably reflecting slow transport, despite the drier climate, which slows chemical weathering rates. Some chemical weathering proxies, such as K/Si or kaolinite/(illite + chlorite), show no temporal evolution, but illite crystallinity and the chemical index of alteration do have statistically measurable decreases over long time periods. Using these proxies, we suggest that sediment alteration was moderate and then increased from 13 to 11 Ma, remained high until 9 Ma, and then reduced from that time until 6 Ma in the context of reduced physical erosion during a time of increasing aridity as tracked by hematite/goethite values. The poorly defined reducing trend in weathering intensity is not clearly linked to global cooling and at least partly reflects regional climate change. Since 6 Ma, weathering has been weak but variable since a final reduction in alteration state after 3.5 Ma that correlates with the onset of Northern Hemispheric glaciation. Reduced or stable chemical weathering at a time of falling sedimentation rates is not consistent with models for Cenozoic global climate change that invoke greater Himalayan weathering fluxes drawing down atmospheric CO2 but are in accord with the idea of greater surface reactivity to weathering.This study was made possible by samples provided by the IODP. The work was partially funded by a grant from The U.S. Science Support Program (USSSP), as well as additional funding from the Charles T. McCord Jr. Endowed Chair in petroleum geology at LSU