Control Of Nonh=holonomic Systems

Many real-world electrical and mechanical systems have velocity-dependent constraints in their dynamic models. For example, car-like robots, unmanned aerial vehicles, autonomous underwater vehicles and hopping robots, etc. Most of these systems can be transformed into a chained form, which is considered as a canonical form of these nonholonomic systems. Hence, study of chained systems ensure their wide applicability. This thesis studied the problem of continuous feed-back control of the chained systems while pursuing inverse optimality and exponential convergence rates, as well as the feed-back stabilization problem under input saturation constraints. These studies are based on global singularity-free state transformations and controls are synthesized from resulting linear systems. Then, the application of optimal motion planning and dynamic tracking control of nonholonomic autonomous underwater vehicles is considered. The obtained trajectories satisfy the boundary conditions and the vehicles\u27 kinematic model, hence it is smooth and feasible. A collision avoidance criteria is set up to handle the dynamic environments. The resulting controls are in closed forms and suitable for real-time implementations. Further, dynamic tracking controls are developed through the Lyapunov second method and back-stepping technique based on a NPS AUV II model. In what follows, the application of cooperative surveillance and formation control of a group of nonholonomic robots is investigated. A designing scheme is proposed to achieves a rigid formation along a circular trajectory or any arbitrary trajectories. The controllers are decentralized and are able to avoid internal and external collisions. Computer simulations are provided to verify the effectiveness of these designs

Physics-based Machine Learning Methods for Control and Sensing in Fish-like Robots

Underwater robots are important for the construction and maintenance of underwater infrastructure, underwater resource extraction, and defense. However, they currently fall far behind biological swimmers such as fish in agility, efficiency, and sensing capabilities. As a result, mimicking the capabilities of biological swimmers has become an area of significant research interest. In this work, we focus specifically on improving the control and sensing capabilities of fish-like robots. Our control work focuses on using the Chaplygin sleigh, a two-dimensional nonholonomic system which has been used to model fish-like swimming, as part of a curriculum to train a reinforcement learning agent to control a fish-like robot to track a prescribed path. The agent is first trained on the Chaplygin sleigh model, which is not an accurate model of the swimming robot but crucially has similar physics; having learned these physics, the agent is then trained on a simulated swimming robot, resulting in faster convergence compared to only training on the simulated swimming robot. Our sensing work separately considers using kinematic data (proprioceptive sensing) and using surface pressure sensors. The effect of a swimming body\u27s internal dynamics on proprioceptive sensing is investigated by collecting time series of kinematic data of both a flexible and rigid body in a water tunnel behind a moving obstacle performing different motions, and using machine learning to classify the motion of the upstream obstacle. This revealed that the flexible body could more effectively classify the motion of the obstacle, even if only one if its internal states is used. We also consider the problem of using time series data from a `lateral line\u27 of pressure sensors on a fish-like body to estimate the position of an upstream obstacle. Feature extraction from the pressure data is attempted with a state-of-the-art convolutional neural network (CNN), and this is compared with using the dominant modes of a Koopman operator constructed on the data as features. It is found that both sets of features achieve similar estimation performance using a dense neural network to perform the estimation. This highlights the potential of the Koopman modes as an interpretable alternative to CNNs for high-dimensional time series. This problem is also extended to inferring the time evolution of the flow field surrounding the body using the same surface measurements, which is performed by first estimating the dominant Koopman modes of the surrounding flow, and using those modes to perform a flow reconstruction. This strategy of mapping from surface to field modes is more interpretable than directly constructing a mapping of unsteady fluid states, and is found to be effective at reconstructing the flow. The sensing frameworks developed as a result of this work allow better awareness of obstacles and flow patterns, knowledge which can inform the generation of paths through the fluid that the developed controller can track, contributing to the autonomy of swimming robots in challenging environments

Accurate IMU Preintegration Using Switched Linear Systems For Autonomous Systems

Employing an inertial measurement unit (IMU) as an additional sensor can dramatically improve both reliability and accuracy of visual/Lidar odometry (VO/LO). Different IMU integration models are introduced using different assumptions on the linear acceleration from the IMU. In this paper, a novel IMU integration model is proposed by using switched linear systems. The proposed approach assumes that both the linear acceleration and the angular velocity in the body frame are constant between two consecutive IMU measurements. This is more realistic in real world situation compared to existing approaches which assume that linear acceleration is constant in the world frame while angular velocity is constant in the body frame between two successive IMU measurements. Experimental results show that the proposed approach outperforms the state-of-the-art IMU integration model. The proposed model is thus important for localization of high speed autonomous vehicles in GPS denied environments.Comment: 19 pages, 2 Figures, Accepted for publication by the IEEE Intelligent Transportation Systems Conference (ITSC 2019). Additionally, Supplementary Derivations on the Pape

Unified Dynamics and Control of a Robot Manipulator Mounted on a VTOL Aircraft Platform

An innovative type of mobile manipulator, designated Manipulator on VTOL (Vertical Take-Off and Landing) Aircraft (MOVA), is proposed as a potential candidate for autonomous execution of field work in less-structured indoor and outdoor environments. Practical use of the MOVA system requires a unified controller that addresses the coupled and complex dynamics of the composite system; especially the interaction of the robotic manipulator with the aircraft airframe. Model-based controller design methods require explicit dynamics models of the MOVA system. Preliminary investigation of a two-dimensional MOVA system toward a dynamics model and controller design is presented in preparation for developing the controller of the more complex MOVA system in 3D space. Dynamics of the planar MOVA system are derived using the Lagrangian approach and then transforming the result into a form that facilitates controller design using the concept of a virtual manipulator. A MOVA end-effector trajectory tracking controller was designed with the transformed dynamics equation using the integrator back-stepping control design framework. Validity of the controller is shown via stability analysis, simulation results, and results from a physical test-bed. A systematic approach is illustrated for the derivation of the 3D MOVA system dynamics equations. The resulting dynamics equations are represented abstractly in the standard robot dynamics form and proven to have the skew-symmetric property, which is a useful property for control derivation. An open source Mathematica program was developed to achieve automatic symbolic derivation of the MOVA system dynamics. Accessory tools were also designed to create a tool-chain that starts with an Autodesk Inventor CAD drawing, generates input to the Mathematica program, and then formats the output for direct use in MATLAB and Simulink. A unified nonlinear control algorithm that controls the 3D MOVA system, including both the aircraft and the onboard manipulator, as a single entity was developed to achieve trajectory tracking of the MOVA end-effector position and attitude based on the explicit dynamics equation. Globally Uniformly Ultimately Bounded (GUUB) stability is proven for the controller using Lyapunov-type stability analysis. Physical testing was constructed in order to to demonstrate the performance of the proposed controller on a MOVA system with a two-link onboard manipulator

Vibration, Control and Stability of Dynamical Systems

From Preface: This is the fourteenth time when the conference “Dynamical Systems: Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and Ministry of Science and Higher Education of Poland. It is a great pleasure that our invitation has been accepted by recording in the history of our conference number of people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcomed over 180 persons from 31 countries all over the world. They decided to share the results of their research and many years experiences in a discipline of dynamical systems by submitting many very interesting papers. This year, the DSTA Conference Proceedings were split into three volumes entitled “Dynamical Systems” with respective subtitles: Vibration, Control and Stability of Dynamical Systems; Mathematical and Numerical Aspects of Dynamical System Analysis and Engineering Dynamics and Life Sciences. Additionally, there will be also published two volumes of Springer Proceedings in Mathematics and Statistics entitled “Dynamical Systems in Theoretical Perspective” and “Dynamical Systems in Applications”

Safe navigation and human-robot interaction in assistant robotic applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Recent Advances in Robust Control

Robust control has been a topic of active research in the last three decades culminating in H_2/H_\infty and \mu design methods followed by research on parametric robustness, initially motivated by Kharitonov's theorem, the extension to non-linear time delay systems, and other more recent methods. The two volumes of Recent Advances in Robust Control give a selective overview of recent theoretical developments and present selected application examples. The volumes comprise 39 contributions covering various theoretical aspects as well as different application areas. The first volume covers selected problems in the theory of robust control and its application to robotic and electromechanical systems. The second volume is dedicated to special topics in robust control and problem specific solutions. Recent Advances in Robust Control will be a valuable reference for those interested in the recent theoretical advances and for researchers working in the broad field of robotics and mechatronics

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Motion control using optical flow of sparse image features

Reactive motion planning and local navigation of robots remains a significant challenge in the motion control of robotic vehicles. This thesis presents new results on vision guided navigation using optical flow. By detecting key image features, calculating optical flow and leveraging time-to-transit (tau) as a feedback signal, control architectures can steer a vehicle so as to avoid obstacles while simultaneously using them as navigation beacons. Averaging and balancing tau over multiple image features successfully guides a vehicle along a corridor while avoiding looming objects in the periphery. In addition, the averaging strategy deemphasizes noise associated with rotationally induced flow fields, mitigating risks of positive feedback akin to the Larsen effect. A recently developed, biologically inspired, binary-key point description algorithm, FReaK, offers process speed-ups that make vision-based feedback signals achievable. A Parrot ARDrone2 has proven to be a reliable platform for testing the architecture and has demonstrated the control law's effectiveness in using time-to-transit calculations for real-time navigation

Contributions to shared control and coordination of single and multiple robots

L’ensemble des travaux présentés dans cette habilitation traite de l'interface entre un d'un opérateur humain avec un ou plusieurs robots semi-autonomes aussi connu comme le problème du « contrôle partagé ».Le premier chapitre traite de la possibilité de fournir des repères visuels / vestibulaires à un opérateur humain pour la commande à distance de robots mobiles.Le second chapitre aborde le problème, plus classique, de la mise à disposition à l’opérateur d’indices visuels ou de retour haptique pour la commande d’un ou plusieurs robots mobiles (en particulier pour les drones quadri-rotors).Le troisième chapitre se concentre sur certains des défis algorithmiques rencontrés lors de l'élaboration de techniques de coordination multi-robots.Le quatrième chapitre introduit une nouvelle conception mécanique pour un drone quadrirotor sur-actionné avec pour objectif de pouvoir, à terme, avoir 6 degrés de liberté sur une plateforme quadrirotor classique (mais sous-actionné).Enfin, le cinquième chapitre présente une cadre général pour la vision active permettant, en optimisant les mouvements de la caméra, l’optimisation en ligne des performances (en terme de vitesse de convergence et de précision finale) de processus d’estimation « basés vision »