Robust Model Predictive Control for Linear Parameter Varying Systems along with Exploration of its Application in Medical Mobile Robots

This thesis seeks to develop a robust model predictive controller (MPC) for Linear Parameter Varying (LPV) systems. LPV models based on input-output display are employed. We aim to improve robust MPC methods for LPV systems with an input-output display. This improvement will be examined from two perspectives. First, the system must be stable in conditions of uncertainty (in signal scheduling or due to disturbance) and perform well in both tracking and regulation problems. Secondly, the proposed method should be practical, i.e., it should have a reasonable computational load and not be conservative. Firstly, an interpolation approach is utilized to minimize the conservativeness of the MPC. The controller is calculated as a linear combination of a set of offline predefined control laws. The coefficients of these offline controllers are derived from a real-time optimization problem. The control gains are determined to ensure stability and increase the terminal set. Secondly, in order to test the system's robustness to external disturbances, a free control move was added to the control law. Also, a Recurrent Neural Network (RNN) algorithm is applied for online optimization, showing that this optimization method has better speed and accuracy than traditional algorithms. The proposed controller was compared with two methods (robust MPC and MPC with LPV model based on input-output) in reference tracking and disturbance rejection scenarios. It was shown that the proposed method works well in both parts. However, two other methods could not deal with the disturbance. Thirdly, a support vector machine was introduced to identify the input-output LPV model to estimate the output. The estimated model was compared with the actual nonlinear system outputs, and the identification was shown to be effective. As a consequence, the controller can accurately follow the reference. Finally, an interpolation-based MPC with free control moves is implemented for a wheeled mobile robot in a hospital setting, where an RNN solves the online optimization problem. The controller was compared with a robust MPC and MPC-LPV in reference tracking, disturbance rejection, online computational load, and region of attraction. The results indicate that our proposed method surpasses and can navigate quickly and reliably while avoiding obstacles

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 »

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Improving Leader-Follower Formation Control Performance for Quadrotors

This thesis aims to improve the leader-follower team formation flight performance of Unmanned Aerial Vehicles (UAVs) by applying nonlinear robust and optimal techniques, in particular the nonlinear H_infinity and the iterative Linear Quadratic Regulator (iLQR), to stabilisation, path tracking and leader-follower team formation control problems. Existing solutions for stabilisation, path tracking and leader-follower team formation control have addressed a linear or nonlinear control technique for a linearised system with limited disturbance consideration, or for a nonlinear system with an obstacle-free environment. To cover part of this area of research, in this thesis, some nonlinear terms were included in the quadrotors' dynamic model, and external disturbance and model parameter uncertainties were considered. Five different controllers were developed. The first and the second controllers, the nonlinear suboptimal H_infinity control technique and the Integral Backstepping (IBS) controller, were based on Lyapunov theory. The H_infinity controller was developed with consideration of external disturbance and model parameter uncertainties. These two controllers were compared for path tracking and leader-follower team formation control. The third controller was the Proportional Derivative square (PD2), which was applied for attitude control and compared with the H_infinity controller. The fourth and the fifth controllers were the Linear Quadratic Regulator (LQR) control technique and the optimal iLQR, which was developed based on the LQR control technique. These were applied for attitude, path tracking and team formation control and there results were compared. Two features regarding the choice of the control technique were addressed: stability and robustness on the one hand, which were guaranteed using the H_infinity control technique as the disturbance is inherent in its mathematical model, and the improvement in the performance optimisation on the other, which was achieved using the iLQR technique as it is based on the optimal LQR control technique. Moreover, one loop control scheme was used to control each vehicle when these controllers were implemented and a distributed control scheme was proposed for the leader-follower team formation problem. Each of the above mentioned controllers was tested and verified in simulation for different predefined paths. Then only the nonlinear H_infinity controller was tested in both simulation and real vehicles experiments

Multiple-vehicle resource-constrained navigation in the deep ocean

Thesis (S.M.)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2011.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 139-148).This thesis discusses sensor management methods for multiple-vehicle fleets of autonomous underwater vehicles, which will allow for more efficient and capable infrastructure in marine science, industry, and naval applications. Navigation for fleets of vehicles in the ocean presents a large challenge, as GPS is not available underwater and dead-reckoning based on inertial or bottom-lock methods can require expensive sensors and suffers from drift. Due to zero drift, acoustic navigation methods are attractive as replacements or supplements to dead-reckoning, and centralized systems such as an Ultra-Short Baseline Sonar (USBL) allow for small and economical components onboard the individual vehicles. Motivated by subsea equipment delivery, we present model-scale proof-of-concept experimental pool tests of a prototype Vertical Glider Robot (VGR), a vehicle designed for such a system. Due to fundamental physical limitations of the underwater acoustic channel, a sensor such as the USBL is limited in its ability to track multiple targets-at best a small subset of the entire fleet may be observed at once, at a low update rate. Navigation updates are thus a limited resource and must be efficiently allocated amongst the fleet in a manner that balances the exploration versus exploitation tradeoff. The multiple vehicle tracking problem is formulated in the Restless Multi-Armed Bandit structure following the approach of Whittle in [108], and we investigate in detail the Restless Bandit Kalman Filters priority index algorithm given by Le Ny et al. in [71]. We compare round-robin and greedy heuristic approaches with the Restless Bandit approach in computational experiments. For the subsea equipment delivery example of homogeneous vehicles with depth-varying parameters, a suboptimal quasi-static approximation of the index algorithm balances low landing error with safety and robustness. For infinite-horizon tracking of systems with linear time-invariant parameters, the index algorithm is optimal and provides benefits of up to 40% over the greedy heuristic for heterogeneous vehicle fleets. The index algorithm can match the performance of the greedy heuristic for short horizons, and offers the greatest improvement for long missions, when the infinite-horizon assumption is reasonably met.by Brooks Louis-Kiguchi Reed.S.M

A COLLISION AVOIDANCE SYSTEM FOR AUTONOMOUS UNDERWATER VEHICLES

The work in this thesis is concerned with the development of a novel and practical collision avoidance system for autonomous underwater vehicles (AUVs). Synergistically, advanced stochastic motion planning methods, dynamics quantisation approaches, multivariable tracking controller designs, sonar data processing and workspace representation, are combined to enhance significantly the survivability of modern AUVs. The recent proliferation of autonomous AUV deployments for various missions such as seafloor surveying, scientific data gathering and mine hunting has demanded a substantial increase in vehicle autonomy. One matching requirement of such missions is to allow all the AUV to navigate safely in a dynamic and unstructured environment. Therefore, it is vital that a robust and effective collision avoidance system should be forthcoming in order to preserve the structural integrity of the vehicle whilst simultaneously increasing its autonomy. This thesis not only provides a holistic framework but also an arsenal of computational techniques in the design of a collision avoidance system for AUVs. The design of an obstacle avoidance system is first addressed. The core paradigm is the application of the Rapidly-exploring Random Tree (RRT) algorithm and the newly developed version for use as a motion planning tool. Later, this technique is merged with the Manoeuvre Automaton (MA) representation to address the inherent disadvantages of the RRT. A novel multi-node version which can also address time varying final state is suggested. Clearly, the reference trajectory generated by the aforementioned embedded planner must be tracked. Hence, the feasibility of employing the linear quadratic regulator (LQG) and the nonlinear kinematic based state-dependent Ricatti equation (SDRE) controller as trajectory trackers are explored. The obstacle detection module, which comprises of sonar processing and workspace representation submodules, is developed and tested on actual sonar data acquired in a sea-trial via a prototype forward looking sonar (AT500). The sonar processing techniques applied are fundamentally derived from the image processing perspective. Likewise, a novel occupancy grid using nonlinear function is proposed for the workspace representation of the AUV. Results are presented that demonstrate the ability of an AUV to navigate a complex environment. To the author's knowledge, it is the first time the above newly developed methodologies have been applied to an A UV collision avoidance system, and, therefore, it is considered that the work constitutes a contribution of knowledge in this area of work.J&S MARINE LT

Adaptive and learning-based formation control of swarm robots

Autonomous aerial and wheeled mobile robots play a major role in tasks such as search and rescue, transportation, monitoring, and inspection. However, these operations are faced with a few open challenges including robust autonomy, and adaptive coordination based on the environment and operating conditions, particularly in swarm robots with limited communication and perception capabilities. Furthermore, the computational complexity increases exponentially with the number of robots in the swarm. This thesis examines two different aspects of the formation control problem. On the one hand, we investigate how formation could be performed by swarm robots with limited communication and perception (e.g., Crazyflie nano quadrotor). On the other hand, we explore human-swarm interaction (HSI) and different shared-control mechanisms between human and swarm robots (e.g., BristleBot) for artistic creation. In particular, we combine bio-inspired (i.e., flocking, foraging) techniques with learning-based control strategies (using artificial neural networks) for adaptive control of multi- robots. We first review how learning-based control and networked dynamical systems can be used to assign distributed and decentralized policies to individual robots such that the desired formation emerges from their collective behavior. We proceed by presenting a novel flocking control for UAV swarm using deep reinforcement learning. We formulate the flocking formation problem as a partially observable Markov decision process (POMDP), and consider a leader-follower configuration, where consensus among all UAVs is used to train a shared control policy, and each UAV performs actions based on the local information it collects. In addition, to avoid collision among UAVs and guarantee flocking and navigation, a reward function is added with the global flocking maintenance, mutual reward, and a collision penalty. We adapt deep deterministic policy gradient (DDPG) with centralized training and decentralized execution to obtain the flocking control policy using actor-critic networks and a global state space matrix. In the context of swarm robotics in arts, we investigate how the formation paradigm can serve as an interaction modality for artists to aesthetically utilize swarms. In particular, we explore particle swarm optimization (PSO) and random walk to control the communication between a team of robots with swarming behavior for musical creation

Design and Development of a Lightweight Ankle Exoskeleton for Human Walking Augmentation

RESUMÉ La plupart des exosquelettes motorisés de la cheville ont une masse distale considérable, ce qui limite leur capacité à réduire l’énergie dépensée par l’utilisateur durant la marche. L’objectif de notre travail est de développer un exosquelette de chevilles avec le minimum de masse distale ajoutée comparé aux exosquelettes motorisés de chevilles existants. Aussi, l’exosquelette doit fournir au moins 50 Nm de support au couple de flexion plantaire. L’exosquelette développé dans le cadre de ce mémoire utilise deux câbles Bowden pour transmettre la force mécanique de l’unité d’actionnement attachée à la taille aux deux tiges en fibre de Carbonne attachées à la botte de l’utilisateur. Quand les deux tiges sont tirées, ils génèrent un couple qui supporte le mouvement de flexion plantaire à la fin de la phase d’appui du cycle de marche. Une pièce conçue sur mesure et imprimé en plastique par prototypage rapide a été attachée au tibia pour ajuster la direction des câbles. Une étude d’optimisation a été effectuée pour minimiser la masse des tiges limitant ainsi la masse distale de l’exosquelette (attaché au tibia et pied) à seulement 348 g. Le résultat principal obtenu à partir des tests de marche est la réduction de l’activité des muscles soléaire et gastrocnémien du sujet par une moyenne de 37% et 44% respectivement lors de la marche avec l’exosquelette comparée à la marche normale. Cette réduction s’est produite quand l’exosquelette a fourni une puissance mécanique de 19 ± 2 W avec un actionnement qui a commencé à 38% du cycle de marche. Ce résultat démontre le potentiel de notre exosquelette à réduire le cout métabolique de marche et souligne l’importance de réduire la masse distale d’un exosquelette de marche.----------ABSTRACT Most of powered ankle exoskeletons add considerable distal mass to the user which limits their capacity to reduce the metabolic energy of walking. The objective of the work presented in this master thesis is to develop an ankle exoskeleton with a minimum added distal mass compared to existing autonomous powered ankle exoskeletons, while providing at least 50 Nm of assistive plantar flexion torque. The exoskeleton developed in this master thesis uses Bowden cables to transmit the mechanical force from the actuation unit attached to the waist to the carbon fiber struts fixed on the boot. As the struts are pulled, they create an assistive ankle plantar flexion torque. A 3D-printed brace was attached to the shin to adjust the direction of the cables. A design optimization study was performed to minimize the mass of the struts, thereby limiting the total added distal mass, attached to the shin and foot, to only 348 g. The main result obtained from walking tests was the reduction of the soleus and gastrocnemius muscles activity by an average of 37% and 44% respectively when walking with the exoskeleton compared to normal walking. This reduction occurred when the exoskeleton delivered a mechanical power of 19 ± 2 W with an actuation onset fixed at 38% of the gait cycle. This result shows the potential of the proposed exoskeleton to reduce the metabolic cost of walking and emphasizes the importance of minimizing the distal mass of ankle exoskeletons