Robust data assimilation in river flow and stage estimation based on multiple imputation particle filter

In this paper, new method is proposed for a more robust Data Assimilation (DA) design of the river flow and stage estimation. By using the new sets of data that are derived from the incorporated Multi Imputation Particle Filter (MIPF) in the DA structure, the proposed method is found to have overcome the issue of missing observation data and contributed to a better estimation process. The convergence analysis of the MIPF is discussed and shows that the number of the particles and imputation influence the ability of this method to perform estimation. The simulation results of the MIPF demonstrated the superiority of the proposed approach when being compared to the Extended Kalman Filter (EKF) and Particle Filter (PF)

Aquatic escape for micro-aerial vehicles

As our world is experiencing climate changes, we are in need of better monitoring technologies. Most of our planet is covered with water and robots will need to move in aquatic environments. A mobile robotic platform that possesses efficient locomotion and is capable of operating in diverse scenarios would give us an advantage in data collection that can validate climate models, emergency relief and experimental biological research. This field of application is the driving vector of this robotics research which aims to understand, produce and demonstrate solutions of aerial-aquatic autonomous vehicles. However, small robots face major challenges in operating both in water and in air, as well as transition between those fluids, mainly due to the difference of density of the media. This thesis presents the developments of new aquatic locomotion strategies at small scales that further enlarge the operational domain of conventional platforms. This comprises flight, shallow water locomotion and the transition in-between. Their operating principles, manufacturing methods and control methods are discussed and evaluated in detail. I present multiple unique aerial-aquatic robots with various water escape mechanisms, spanning over different scales. The five robotic platforms showcased share similarities that are compared. The take-off methods are analysed carefully and the underlying physics principles put into light. While all presented research fulfils a similar locomotion objective - i.e aerial and aquatic motion - their relevance depends on the environmental conditions and supposed mission. As such, the performance of each vehicle is discussed and characterised in real, relevant conditions. A novel water-reactive fuel thruster is developed for impulsive take-off, allowing consecutive and multiple jump-gliding from the water surface in rough conditions. At a smaller scale, the escape of a milligram robotic bee is achieved. In addition, a new robot class is demonstrated, that employs the same wings for flying as for passive surface sailing. This unique capability allows the flexibility of flight to be combined with long-duration surface missions, enabling autonomous prolonged aquatic monitoring.Open Acces

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field

Autonomous Sailboat Navigation

The purpose of this study was to investigate novel methods on an unmanned sailing boat, which enables it to sail fully autonomously, navigate safely, and perform long-term missions. The author used robotic sailing boat prototypes for field experiments as his main research method. Two robotic sailing boats have been developed especially for this purpose. A compact software model of a sailing boat's behaviour allowed for further evaluation of routing and obstacle avoidance methods in a computer simulation. The results of real-world experiments and computer simulations are validated against each other. It has been demonstrated that autonomous boat sailing is possible by the effective combination of appropriate new and novel techniques that will allow autonomous sailing boats to create appropriate routes, to react properly on obstacles and to carry out sailing manoeuvres by controlling rudder and sails. Novel methods for weather routing, collision avoidance, and autonomous manoeuvre execution have been proposed and successfully demonstrated. The combination of these techniques in a layered hybrid subsumption architecture make robotic sailing boats a promising tool for many applications, especially in ocean observation

From Rousettus aegyptiacus (bat) Landing to Robotic Landing: Regulation of CG-CP Distance Using a Nonlinear Closed-Loop Feedback

Bats are unique in that they can achieve unrivaled agile maneuvers due to their functionally versatile wing conformations. Among these maneuvers, roosting (landing) has captured attentions because bats perform this acrobatic maneuver with a great composure. This work attempts to reconstruct bat landing maneuvers with a Micro Aerial Vehicle (MAV) called Allice. Allice is capable of adjusting the position of its Center of Gravity (CG) with respect to the Center of Pressure (CP) using a nonlinear closed-loop feedback. This nonlinear control law, which is based on the method of input-output feedback linearization, enables attitude regulations through variations in CG-CP distance. To design the model-based nonlinear controller, the Newton-Euler dynamic model of the robot is considered, in which the aerodynamic coefficients of lift and drag are obtained experimentally. The performance of the proposed control architecture is validated by conducting several experiments

Design of a Mobile Underwater Charging System

Autonomous Underwater Vehicles (AUVs) are extremely capable vehicles for numerous ocean related missions. AUVs are energy limited, resulting in short mission endurance on the scale of hours to days. Underwater Gliders (UGs) are able to operate on the order of months to years by using nontraditional propulsion methods. UGs, however, are unable to perform missions requiring high speed or direct forward motion due to the nature of their buoyancy driven motion. This work reviews the current state of the art in recharging AUVs and offers an underwater recharging network concept at a significantly reduced cost to traditional methods. The solution includes the design of a UG capable of serving as charge carrying agent that couples with and charges AUVs autonomously. The vehicle design is built on the work done previously at the Nonlinear and Autonomous Systems Lab on the development of ROUGHIE (Research Oriented Underwater Glider for Hands-on Investigative Engineering). The ROUGHIE2 design is a rethinking of the original ROUGHIE capabilities to serve as a mobile charger by increasing depth rating, endurance, and payload capacity. The recharging concept presented will be easy to adapt to many different AUVs and UGs making this technology universal to small AUVs

A remote anomaly detection system for Slocum underwater gliders

Marine Autonomous Systems (MAS) operating at sea beyond visual line of sight need to be self-reliant, as any malfunction could lead to loss or pose a risk to other sea users. In the absence of fully automated on-board control and fault detection tools, MAS are piloted and monitored by experts, resulting in high operational costs and limiting the scale of observational fleets that can be deployed simultaneously. Hence, an effective anomaly detection system is fundamental to increase fleet capacity and reliability. In this study, an on-line, remote fault detection system is developed for underwater gliders. Two alternative methods are analysed using time series data: feedforward deep neural networks estimating the glider’s vertical velocity and an autoencoder. The systems are trained using field data from four baseline deployments of Slocum gliders and tested on six deployments of vehicles suffering from adverse behaviour. The methods are able to successfully detect a range of anomalies in the near real time data streams, whilst being able to generalise to different glider configurations. The autoencoder’s error in reconstructing the original signals is the clearest indicator of anomalies. Thus, the autoencoder is a prime candidate to be included into an all-encompassing condition monitoring system for MAS

Closed-loop nonlinear optimal control design for flapping-wing flying robot (1.6 m wingspan) in indoor confined space: Prototyping, modeling, simulation, and experiment

This is an open access article under the CC BY license (http://creativecommons.org/ licenses/by/4.0/).The flapping-wing technology has emerged recently in the application of unmanned aerial robotics for autonomous flight, control, inspection, monitoring, and manipulation. Despite the advances in applications and outdoor manual flights (open-loop control), closed-loop control is yet to be investigated. This work presents a nonlinear optimal closed-loop control design via the state-dependent Riccati equation (SDRE) for a flapping-wing flying robot (FWFR). Considering that the dynamic modeling of the flapping-wing robot is complex, a proper model for the implementation of nonlinear control methods is demanded. This work proposes an alternative approach to deliver an equivalent dynamic for the translation of the system and a simplified model for orientation, to find equivalent dynamics for the whole system. The objective is to see the effect of flapping (periodic oscillation) on behavior through a simple model in simulation. Then the SDRE controller is applied to the derived model and implemented in simulations and experiments. The robot bird is a 1.6 m wingspan flapping-wing system (six-degree-of-freedom robot) with four actuators, three in the tail, and one as the flapping input. The underactuated system has been controlled successfully in position and orientation. The control loop is closed by the motion capture system in the indoor test bed where the experiments of flight have been successfully done