Papers by Felipe Andres Marchant Gonzalez
Drones
Autonomous Unmanned Aerial Vehicles (UAV) for planetary exploration missions require increased on... more Autonomous Unmanned Aerial Vehicles (UAV) for planetary exploration missions require increased onboard mission-planning and decision-making capabilities to access full operational potential in remote environments (e.g., Antarctica, Mars or Titan). However, the uncertainty introduced by the environment and the limitation of available sensors has presented challenges for planning such missions. Partially Observable Markov Decision Processes (POMDPs) are commonly used to enable decision-making and mission-planning processes that account for environmental, perceptional (extrinsic) and actuation (intrinsics) uncertainty. Here, we propose the UAV4PE framework, a testing framework for autonomous UAV missions using POMDP formulations. This framework integrates modular components for simulation, emulation, UAV guidance, navigation and mission planning. State-of-the-art tools such as python, C++, ROS, PX4 and JuliaPOMDP are employed by the framework, and we used python data-science libraries ...
International Journal of Environmental Research and Public Health
Syndromic surveillance data were used to estimate the direct impact of air pollution on healthcar... more Syndromic surveillance data were used to estimate the direct impact of air pollution on healthcare-seeking behaviour, between 1 April 2012 and 31 December 2017. A difference-in-differences approach was used to control for spatial and temporal variations that were not due to air pollution and a meta-analysis was conducted to combine estimates from different pollution periods. Significant increases were found in general practitioner (GP) out-of-hours consultations, including a 98% increase (2–386, 95% confidence interval) in acute bronchitis and a 16% (3–30) increase in National Health Service (NHS) 111 calls for eye problems. However, the numbers involved are small; for instance, roughly one extra acute bronchitis consultation in a local authority on a day when air quality is poor. These results provide additional information for healthcare planners on the impacts of localised poor air quality. However, further work is required to identify the separate impact of different pollutants.
2017 IEEE Aerospace Conference, 2017
Visual servoing of a quadrotor with suspended slung load for object detection and tracking. In Ma... more Visual servoing of a quadrotor with suspended slung load for object detection and tracking. In Mattingly, R (Ed.
2017 IEEE Aerospace Conference, 2017
In recent years, a phenomenal increase in the development of Unmanned Aerial Vehicles (UAVs) has ... more In recent years, a phenomenal increase in the development of Unmanned Aerial Vehicles (UAVs) has been observed in a broad range of applications in various fields of study. Precision agriculture has emerged as a major field of interest, integrating unmanned monitoring of crop health into general agricultural practices for researchers are utilizing UAV to collect data for post-analysis. This paper describes a modular and generic system that is able to control the UAV using computer vision. A configuration approach similar to the Observation, Orientation, Decision and Action (OODA) loop has been implemented to allow the system to perform on-board decision making. The detection of an object of interest is performed by computer vision functionality. This allows the UAV to change its planned path accordingly and approach the target in order to perform a close inspection, or conduct a manoeuvres such as the application of herbicide or collection of higher resolution agricultural images.
Sensors (Basel, Switzerland), Jan 22, 2018
The environmental and economic impacts of exotic fungal species on natural and plantation forests... more The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests. This paper proposes a framework that consolidates site-based insights and remote sensing capabilities to detect and segment deteriorations by fungal pathogens in natural and plantation forests. This approach is illustrated with an experimentation case of myrtle rust () on paperbark tea trees () in New South Wales (NSW), Australia. The method integrates unmanned aerial vehicles (UAVs), hyperspectral...
Sensors (Basel, Switzerland), Jan 16, 2018
The monitoring of invasive grasses and vegetation in remote areas is challenging, costly, and on ... more The monitoring of invasive grasses and vegetation in remote areas is challenging, costly, and on the ground sometimes dangerous. Satellite and manned aircraft surveys can assist but their use may be limited due to the ground sampling resolution or cloud cover. Straightforward and accurate surveillance methods are needed to quantify rates of grass invasion, offer appropriate vegetation tracking reports, and apply optimal control methods. This paper presents a pipeline process to detect and generate a pixel-wise segmentation of invasive grasses, using buffel grass (Cenchrus ciliaris) and spinifex (Triodia sp.) as examples. The process integrates unmanned aerial vehicles (UAVs) also commonly known as drones, high-resolution red, green, blue colour model (RGB) cameras, and a data processing approach based on machine learning algorithms. The methods are illustrated with data acquired in Cape Range National Park, Western Australia (WA), Australia, orthorectified in Agisoft Photoscan Pro, ...
Sensors, 2017
The increased technological developments in Unmanned Aerial Vehicles (UAVs) combined with artific... more The increased technological developments in Unmanned Aerial Vehicles (UAVs) combined with artificial intelligence and Machine Learning (ML) approaches have opened the possibility of remote sensing of extensive areas of arid lands. In this paper, a novel approach towards the detection of termite mounds with the use of a UAV, hyperspectral imagery, ML and digital image processing is intended. A new pipeline process is proposed to detect termite mounds automatically and to reduce, consequently, detection times. For the classification stage, several ML classification algorithms' outcomes were studied, selecting support vector machines as the best approach for their role in image classification of pre-existing termite mounds. Various test conditions were applied to the proposed algorithm, obtaining an overall accuracy of 68%. Images with satisfactory mound detection proved that the method is "resolution-dependent". These mounds were detected regardless of their rotation and position in the aerial image. However, image distortion reduced the number of detected mounds due to the inclusion of a shape analysis method in the object detection phase, and image resolution is still determinant to obtain accurate results. Hyperspectral imagery demonstrated better capabilities to classify a huge set of materials than implementing traditional segmentation methods on RGB images only.
Progress in Aerospace Sciences, 2012
This paper presents a review of existing and current developments and the analysis of Hybrid-Elec... more This paper presents a review of existing and current developments and the analysis of Hybrid-Electric Propulsion Systems (HEPS) for small fixed-wing Unmanned Aerial Vehicles (UAV). In recent years, development of UAV has become a significant growing segment of the global aviation industry. These vehicles are developed with the intention of operating in regions where the presence of onboard human pilots is either too risky or unnecessary. Their popularity with both the military and civilian sectors has seen the use of UAVs in a diverse range of applications, from reconnaissance and surveillance tasks for the military, to civilian uses such as aid relief and monitoring tasks. Efficient energy utilisation on an UAV is essential to its functioning, often to achieve the operational goals of range, endurance and other specific mission requirements. Due to the limitations of the space available and the mass budget on the UAV, it is often a delicate balance between the onboard energy available (i.e. fuel) and achieving the operational goals. One technology with potential in this area is with the use of HEPS. In this paper, information on the state-of-art technology in this field of research is provided. A description and simulation of a parallel HEPS for a small fixed-wing UAV by incorporating an Ideal Operating Line (IOL) control strategy is described. Simulation models of the components in a HEPS were designed in the MATLAB Simulink environment. An IOL analysis of an UAV piston engine was used to determine the most efficient points of operation for this engine. The results show that an UAV equipped with this HEPS configuration described in this paper is capable of achieving a fuel saving of 6.5%, compared to the engine-only configuration. NOMENCLATURE ACM Aircraft Control Module BSFC Brake specific fuel consumption CBN Charge Battery Now module CMAC Cerebellar model arithmetic computer COTS Commercially-off-the-shelf
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016
In this paper we describe and flight test a novel system architecture for low cost muti-rotor unm... more In this paper we describe and flight test a novel system architecture for low cost muti-rotor unmanned aerial vehicles (UAVs) for searching, tracking and following a ground target. The UAV uses only on-board sensors for localisation within a GPS-denied space with obstacles. This mission is formulated as a Partially Observable Markov Decision Process (POMDP) and uses a modular framework that runs on the Robotic Operating System (ROS). This system computes a policy for executing actions instead of way-points to navigate and avoid obstacles. Results indicate that the system is robust to overcome uncertainties in localisation of both, the aircraft and the target and avoids collisions with the obstacles.
2016 IEEE Aerospace Conference, 2016
There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation fro... more There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.
2016 IEEE Aerospace Conference, 2016
The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ... more The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing onboard decision making.
2016 IEEE Aerospace Conference, 2016
There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and fer... more There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target's GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new waypoint for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.
2016 IEEE Aerospace Conference, 2016
There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge du... more There are some scenarios in which Unmmaned Aerial Vehicle (UAV) navigation becomes a challenge due to the occlusion of GPS systems signal, the presence of obstacles and constraints in the space in which a UAV operates. An additional challenge is presented when a target whose location is unknown must be found within a confined space. In this paper we present a UAV navigation and target finding mission, modelled as a Partially Observable Markov Decision Process (POMDP) using a state-of-the-art online solver in a real scenario using a low cost commercial multi rotor UAV and a modular system architecture running under the Robotic Operative System (ROS). Using POMDP has several advantages to conventional approaches as they take into account uncertainties in sensor information. We present a framework for testing the mission with simulation tests and real flight tests in which we model the system dynamics and motion and perception uncertainties. The system uses a quad-copter aircraft with an board downwards looking camera without the need of GPS systems while avoiding obstacles within a confined area. Results indicate that the system has 100% success rate in simulation and 80% rate during flight test for finding targets located at different locations.
Sensors (Basel, Switzerland), Jan 28, 2015
This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonom... more This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.
47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition, 2009
Game strategies have been developed in past decades and used in the field of economics, engineeri... more Game strategies have been developed in past decades and used in the field of economics, engineering, computer science and biology due to their efficiency in solving design optimisation problems. In addition, research on Multi-Objective (MO) and Multidisciplinary Design Optimisation (MDO) has focused on developing robust and efficient optimisation method to produce quality solutions with less computational time. In this paper, a new optimisation method Hybrid Game Strategy for MO problems is introduced and compared to CMA-ES based optimisation approach. Numerical results obtained from both optimisation methods are compared in terms of computational expense and model quality. The benefits of using Game-strategies are demonstrated.
2013 IEEE International Conference on Robotics and Automation, 2013
Exploiting wind-energy is one possible way to extend the flight duration of an Unmanned Aerial Ve... more Exploiting wind-energy is one possible way to extend the flight duration of an Unmanned Aerial Vehicle. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain, timevarying wind fields and plan a path through them that exploits the energy the field provides. A Gaussian distribution is used to determine uncertainty in the time-varying wind fields. We use a Markov Decision Process to plan a path based upon the uncertainty of the Gaussian distribution. Simulation results are presented to compare the direct line of flight between a start and target point with our planned path for energy consumption and time of travel. The result of our method is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.
IEEE Transactions on Evolutionary Computation, 2013
(2013) FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on... more (2013) FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning. IEEE Transactions on Evolutionary Computation, 17 (2), pp. 272-281.
Felipe (2012) Design, simulation and analysis of a parallel hybrid electric propulsion system for... more Felipe (2012) Design, simulation and analysis of a parallel hybrid electric propulsion system for unmanned aerial vehicles. In
The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial... more The aim of this paper is to implement a Game-Theory based offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most realworld optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. The goal of this work is then to develop a Multi-Objective (MO) optimisation tool able to provide a set of optimal solutions for the inspection task, given the environment data, the mission requirements and the definition of the objectives to minimise. Results indicate the robustness and capability of the method to find the trade-off between the Paretooptimal solutions.
Notice: Changes introduced as a result of publishing processes such as copy-editing and formattin... more Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document.
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Papers by Felipe Andres Marchant Gonzalez