Manoeuvring simulations of Autonomous Underwater Vehicle using quaternion

The dynamics of an autonomous underwater vehicle (AUV), which can perform manoeuvres with pitch angles in the range of 90° is investigated in this paper. The purpose of the AUV is to perform station keeping manoeuvre at about 90° pitch angle by varying propeller revolution. The AUV is launched / retrieved in horizontal orientation.  Quaternion mathematics, 4 quadrant propeller open water characteristics and PID controller for propeller revolution are incorporated in manoeuvring mathematical model for this purpose.  A procedure for optimizing the gain coefficients for the PID controller is developed using the manoeuvring mathematical model. Two design configuration of the AUV are investigated, positively buoyant and negatively buoyant. It is shown that both the optimal gain coefficients for the PID controller for propeller revolution and dynamic response of the AUV are different for each design configuration.&nbsp

Aircraft manoeuvring for sensor aiming

Airborne sensor aiming can be achieved with a fixed sensor using the manoeuvrability of an aircraft. Such a method offers advantages in potential sensor coverage and reduced payload complexity. Without use of a gimbal, an aircraft can be made more robust and sensor aiming is limited only by the aircraft flight capabilities. A novel method is developed and demonstrated for performing sensor aiming with a fixed-wing aircraft. A creative mathematical framework is presented for both a 3D path following controller and a method to seamlessly achieve sensor aiming while minimizing path deviation. A simulation environment is developed based on a fit-forpurpose aircraft model identified from live flight testing and the control algorithms are validated. Flight test data is presented demonstrating efficacy of the 3D path following controller. These demonstrations also serve to validate the aircraft modelling approach taken during controller development. Two application examples involving airborne radar aiming for detect and avoid and gimbal-less ground target tracking are used to illustrate the sensor aiming method. The proposed sensor aiming methodology is both practical and feasible as supported by results. The proposed method is applicable to both unmanned and manned aircraft. Future work involving the concept of manoeuvrable sensors is proposed in the conclusion

Path planning and reactive based control for a quadrotor with a suspended load

This paper presents a solution to quadrotor cargo transportation, more precisely when cargo is suspended as a sling load. The challenge lies in payload position control and swing attenuation, which we approach by dividing the model into subsystems: attitude quadrotor in free flight, and translational and attitude load dynamics. We propose a solution based on reactive control, in the sense that we utilize a reactive force that reacts to the error position and the oscillation in the load. Asymptotic stability of the system's closed-loop equilibrium is proved using Lyapunov theory. Additionally, a three-dimensional path planning algorithm is proposed based on cubic splines, which give us a natural path between initial and final desired points. Moreover, we convert the path planning problem into trajectory tracking with a spline's correct parametrization. Control and path planning performance are demonstrated with numerical simulations in three different scenarios

Adaptive and Optimal Motion Control of Multi-UAV Systems

This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations and experiments on a multi-quadrotor UAV system testbed

Embedded avionics with Kalman state estimation for a novel micro-scale unmanned aerial vehicle

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis. "June 2013."Includes bibliographical references (pages 107-109).An inertial navigation system leveraging Kalman estimation techniques and quaternion dynamics is developed for deployment to a micro-scale unmanned aerial vehicle (UAV). The capabilities, limitations, and requirements of existing navigation solutions motivate the need for an integrated solution that can be readily applied to small embedded systems and still provide reasonably accurate results. Methods to calibrate and compensate systemic inaccuracies in microelectromechanical systems (MEMS) sensors, commonly used in micro-scale UAV applications, are also developed. The problems associated with attitude determination and system localization are analyzed in isolation with incremental simulation and field testing. Performance is evaluated against commercially available inertial navigation system solutions. The result is a capable navigation system that, by its structure, trades a small measure of accuracy in order to be easily adapted to the embedded computing constraints of unmanned vehicles in the micro-scale.by Theodore Tzanetos.M. Eng

Enhancing 3D Autonomous Navigation Through Obstacle Fields: Homogeneous Localisation and Mapping, with Obstacle-Aware Trajectory Optimisation

Small flying robots have numerous potential applications, from quadrotors for search and rescue, infrastructure inspection and package delivery to free-flying satellites for assistance activities inside a space station. To enable these applications, a key challenge is autonomous navigation in 3D, near obstacles on a power, mass and computation constrained platform. This challenge requires a robot to perform localisation, mapping, dynamics-aware trajectory planning and control. The current state-of-the-art uses separate algorithms for each component. Here, the aim is for a more homogeneous approach in the search for improved efficiencies and capabilities. First, an algorithm is described to perform Simultaneous Localisation And Mapping (SLAM) with physical, 3D map representation that can also be used to represent obstacles for trajectory planning: Non-Uniform Rational B-Spline (NURBS) surfaces. Termed NURBSLAM, this algorithm is shown to combine the typically separate tasks of localisation and obstacle mapping. Second, a trajectory optimisation algorithm is presented that produces dynamically-optimal trajectories with direct consideration of obstacles, providing a middle ground between path planners and trajectory smoothers. Called the Admissible Subspace TRajectory Optimiser (ASTRO), the algorithm can produce trajectories that are easier to track than the state-of-the-art for flight near obstacles, as shown in flight tests with quadrotors. For quadrotors to track trajectories, a critical component is the differential flatness transformation that links position and attitude controllers. Existing singularities in this transformation are analysed, solutions are proposed and are then demonstrated in flight tests. Finally, a combined system of NURBSLAM and ASTRO are brought together and tested against the state-of-the-art in a novel simulation environment to prove the concept that a single 3D representation can be used for localisation, mapping, and planning

Estimated Aerodynamic Forces and Moments and Optimal Orientation of the V-Bat Airframe During Vertical Landing in Gusty Conditions

Ship based Unmanned Air Systems (UAS) are an important tool used by the United States Navy for situational awareness and short-range operations. Naval UAS are used to provide real-time intelligence, surveillance, reconnaissance, and target-acquisition while being low cost, mission flexible, and safe. Unfortunately UAS suffer disadvantages with respect to adverse environmental conditions caused by the air being displaced by the ship. The accumulation of one or more adverse conditions is known as airwake. To counteract the effects of airwake, the objectives of this work are to first evaluate the effect of forces and moments during the vertical landing phase of an aircraft model and second identify the vertical landing path that will minimize the forces and moments acting on the aircraft model. To accomplish these objectives, an overview of the aircraft models component’s mass and aerodynamic properties are given. An overview of the V-BAT UAV model and prescribed landing trajectories are discussed. The V-BAT model is simulated over a sweep of bank angles and altitudes. The simulation force and moment data are evaluated using two methods. The first method evaluates the average and standard deviation of the forces and moments at each altitude and bank angle. The second method creates contour plots of the bank angles that minimize the forces and moments acting on the V-BAT model at each altitude and time step. The results show, during landing, the forces and moments are minimised by following a series of bank angles taken from the minimum force and moment contour plot data

Kinematics and Robot Design I, KaRD2018

This volume collects the papers published on the Special Issue “Kinematics and Robot Design I, KaRD2018” (https://www.mdpi.com/journal/robotics/special_issues/KARD), which is the first issue of the KaRD Special Issue series, hosted by the open access journal “MDPI Robotics”. The KaRD series aims at creating an open environment where researchers can present their works and discuss all the topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”. KaRD2018 received 22 papers and, after the peer-review process, accepted only 14 papers. The accepted papers cover some theoretical and many design/applicative aspects

Trajectory generation for autonomous unmanned aircraft using inverse dynamics

The problem addressed in this research is the in-flight generation of trajectories for autonomous unmanned aircraft, which requires a method of generating pseudo-optimal trajectories in near-real-time, on-board the aircraft, and without external intervention. The focus of this research is the enhancement of a particular inverse dynamics direct method that is a candidate solution to the problem. This research introduces the following contributions to the method. A quaternion-based inverse dynamics model is introduced that represents all orientations without singularities, permits smooth interpolation of orientations, and generates more accurate controls than the previous Euler-angle model. Algorithmic modifications are introduced that: overcome singularities arising from parameterization and discretization; combine analytic and finite difference expressions to improve the accuracy of controls and constraints; remove roll ill-conditioning when the normal load factor is near zero, and extend the method to handle negative-g orientations. It is also shown in this research that quadratic interpolation improves the accuracy and speed of constraint evaluation. The method is known to lead to a multimodal constrained nonlinear optimization problem. The performance of the method with four nonlinear programming algorithms was investigated: a differential evolution algorithm was found to be capable of over 99% successful convergence, to generate solutions with better optimality than the quasi- Newton and derivative-free algorithms against which it was tested, but to be up to an order of magnitude slower than those algorithms. The effects of the degree and form of polynomial airspeed parameterization on optimization performance were investigated, and results were obtained that quantify the achievable optimality as a function of the parameterization degree. Overall, it was found that the method is a potentially viable method of on-board near- real-time trajectory generation for unmanned aircraft but for this potential to be realized in practice further improvements in computational speed are desirable. Candidate optimization strategies are identified for future research.EThOS - Electronic Theses Online ServiceGBUnited Kingdo