Displacement Analysis of Under-Constrained Cable-Driven Parallel Robots

This dissertation studies the geometric static problem of under-constrained cable-driven parallel robots (CDPRs) supported by n cables, with n ≤ 6. The task consists of determining the overall robot configuration when a set of n variables is assigned. When variables relating to the platform posture are assigned, an inverse geometric static problem (IGP) must be solved; whereas, when cable lengths are given, a direct geometric static problem (DGP) must be considered. Both problems are challenging, as the robot continues to preserve some degrees of freedom even after n variables are assigned, with the final configuration determined by the applied forces. Hence, kinematics and statics are coupled and must be resolved simultaneously. In this dissertation, a general methodology is presented for modelling the aforementioned scenario with a set of algebraic equations. An elimination procedure is provided, aimed at solving the governing equations analytically and obtaining a least-degree univariate polynomial in the corresponding ideal for any value of n. Although an analytical procedure based on elimination is important from a mathematical point of view, providing an upper bound on the number of solutions in the complex field, it is not practical to compute these solutions as it would be very time-consuming. Thus, for the efficient computation of the solution set, a numerical procedure based on homotopy continuation is implemented. A continuation algorithm is also applied to find a set of robot parameters with the maximum number of real assembly modes for a given DGP. Finally, the end-effector pose depends on the applied load and may change due to external disturbances. An investigation into equilibrium stability is therefore performed

Position analysis based on multi-affine formulations

Aplicat embargament des de la data de defensa fins el 31/5/2022The position analysis problem is a fundamental issue that underlies many problems in Robotics such as the inverse kinematics of serial robots, the forward kinematics of parallel robots, the coordinated manipulation of objects, the generation of valid grasps, the constraint-based object positioning, the simultaneous localization and map building, and the analysis of complex deployable structures. It also arises in other fields, such as in computer aided design, when the location of objects in a design is given in terms of geometric constrains, or in the conformational analysis of biomolecules. The ubiquity of this problem, has motivated an intense quest for methods able of tackling it. Up to now, efficient algorithms for the general problem have remained elusive and they are only available for particular cases. Moreover, the complexity of the problem has typically led to methods difficult to be implemented. Position analysis can be decomposed into two equally important steps: obtaining a set of closure equations, and solving them. This thesis deals with both of them to obtain a general, simple, and yet efficient solution method that we call the trapezoid method. The first step is addressed relying on dual quaternions. Although it has not been properly highlighted in the past, the use of dual quaternions permits expressing the closure condition of a kinematic loop involving only lower pairs as a system of multi-affine equations. In this thesis, this property is leveraged to introduce an interval-based method specially tailored for solving multi-affine systems. The proposed method is objectively simpler (in the sense that it is easier to understand and to implement) than previous methods based on general techniques such as interval Newton methods, conversions to Bernstein basis, or linear relaxations. Moreover, it relies on two simple operations, namely, linear interpolations and projections on coordinate planes, which can be executed with a high performance. The result is a method that accurately and efficiently bounds the valid solutions of the problem at hand. To further improve the accuracy, we propose the use of redundant, multi affine equations that are derived from the minimal set of equations describing the problem. To improve the efficiency, we introduce a variable elimination methodology that preserves the multi-affinity of the system of equations. The generality and the performance of the proposed trapezoid method are extensively evaluated on different kind of mechanisms, including spherical mechanisms, generic 6R and 7R loops, over-constrained systems, and multi-loop mechanisms. The proposed method is, in all cases, significantly faster than state of the art alternatives.El problema de l'anàlisi de posició és un tema fonamental que subjau a molts problemes de la robòtica, com ara la cinemàtica inversa de robots sèrie, la cinemàtica directa de robots paral·lels, la manipulació coordinada d'objectes, la generació de prensions vàlides amb mans robòtiques, el posicionament d'objectes basat en restriccions, la localització i la creació de mapes de forma simultània, i l'anàlisi d'estructures desplegables complexes. També sorgeix en altres camps, com ara en el disseny assistit per ordinador, quan la ubicació dels objectes en un disseny es dóna en termes de restriccions geomètriques o en l'anàlisi conformacional de biomolècules. La omnipresència d'aquest problema ha motivat una intensa recerca de mètodes capaços d'afrontar-lo. Fins al moment, els algoritmes eficients per al problema general han estat esquius i només estan disponibles per a casos particulars. A més, la complexitat del problema normalment ha conduït a mètodes difícils d'implementar. L'anàlisi de posició es pot descompondre en dos passos igualment importants: l'obtenció d'un sistema d'equacions de tancament i la resolució d'aquest sistema. Aquesta tesi tracta de tots dos passos per tal d'obtenir un mètode de solució general, senzill i alhora eficient que anomenem el mètode del trapezoide. El primer pas s'aborda utilitzant quaternions duals. Tot i que no ha estat suficientment destacat en el passat, l'ús de quaternions duals permet expressar la condició de tancament d'un bucle cinemàtic que impliqui només parells inferiors com a un sistema d'equacions multi-afins. En aquesta tesi s'aprofita aquesta propietat per introduir un mètode especialment dissenyat per resoldre sistemes multi-afins. El mètode proposat és objectivament més senzill (en el sentit que és més fàcil d'entendre i d'implementar) que els mètodes anteriors que utilitzen tècniques generals com ara els mètodes de Newton basats en intervals, les conversions a la base de Bernstein o les relaxacions lineals. A més, el mètode es basa en dues operacions simples, a saber, les interpolacions lineals i les projeccions en plans de coordenades, que es poden executar de forma molt eficient. El resultat és un mètode que acota amb precisió i eficiència les solucions vàlides del problema. Per millorar encara més la precisió, proposem l'ús d'equacions multi-afins redundants derivades del conjunt mínim d'equacions que descriuen el problema. Per altra banda, per millorar l'eficiència, introduïm un metodologia d'eliminació de variables que preserva la multi-afinitat del sistema d'equacions. La generalitat i el rendiment del mètode del trapezoide s'avalua extensivament en diferents tipus de mecanismes, inclosos els mecanismes esfèrics, bucles 6R i 7R genèrics, sistemes sobre-restringits i mecanismes de múltiples bucles. El mètode proposat és, en tots els casos, significativament més ràpid que els mètodes alternatius descrits en la literatura fins al moment.Postprint (published version

On a Jansen leg with multiple gait patterns for reconfigurable walking platforms

Legged robots are able to move across irregular terrains and those based on 1-degree-of-freedom planar linkages can be energy efficient, but are often constrained by a limited range of gaits which can limit their locomotion capabilities considerably. This article reports the design of a novel reconfigurable Theo Jansen linkage that produces a wide variety of gait cycles, opening new possibilities for innovative applications. The suggested mechanism switches from a pin-jointed Grübler kinematic chain to a 5-degree-of-freedom mechanism with slider joints during the reconfiguration process. It is shown that such reconfigurable linkage significantly extend the capabilities of the original design, while maintaining its mechanical simplicity during normal operation, to not only produce different useful gait patterns but also to realize behaviors beyond locomotion. Experiments with an implemented prototype are presented, and their results validate the proposed approach

Model-based Control of Upper Extremity Human-Robot Rehabilitation Systems

Stroke rehabilitation technologies have focused on reducing treatment cost while improving effectiveness. Rehabilitation robots are generally developed for home and clinical usage to: 1) deliver repetitive and stimulating practice to post-stroke patients, 2) minimize therapist interventions, and 3) increase the number of patients per therapist, thereby decreasing the associated cost. The control of rehabilitation robots is often limited to black- or gray-box approaches; thus, safety issues regarding the human-robot interaction are not easily considered. Furthermore, despite numerous studies of control strategies for rehabilitation, there are very few rehabilitation robots in which the tasks are implemented using optimal control theory. Optimal controllers using physics-based models have the potential to overcome these issues. This thesis presents advanced impedance- and model-based controllers for an end-effector-based upper extremity stroke rehabilitation robot. The final goal is to implement a biomechanically-plausible real-time nonlinear model predictive control for the studied rehabilitation system. The real-time term indicates that the controller computations finish within the sampling frequency time. This control structure, along with advanced impedance-based controllers, can be applied to any human-environment interactions. This makes them promising tools for different types of assistive devices, exoskeletons, active prostheses and orthoses, and exercise equipment. In this thesis, a high-fidelity biomechatronic model of the human-robot interaction is developed. The rehabilitation robot is a 2 degree-of-freedom parallelogram linkage with joint friction and backlash, and nonlinear dynamics. The mechatronic model of the robot with relatively accurate identified dynamic parameters is used in the human-robot interaction plant. Different musculoskeletal upper extremity, biomechanic, models are used to model human body motions while interacting with the rehabilitation robot model. Human-robot interaction models are recruited for model-in-loop simulations, thereby tuning the developed controllers in a structured resolution. The interaction models are optimized for real-time simulations. Thus, they are also used within the model-based control structures to provide biofeedback during a rehabilitation therapy. In robotic rehabilitation, because of physical interaction of the patient with a mechanical device, safety is a fundamental element in the design of a controller. Thus, impedance-based assistance is commonly used for robotic rehabilitation. One of our objectives is to achieve a reliable and real-time implementable controller. In our definition, a reliable controller is capable of handling variable exercises and admittance interactions. The controller should reduce therapist intervention and improve the quality of the rehabilitation. Hence, we develop advanced impedance-based assistance controllers for the rehabilitation robot. Overall, two types of impedance-based (i.e., hybrid force-impedance and optimal impedance) controllers are developed and tuned using model-in-loop simulations. Their performances are assessed using simulations and/or experiments. Furthermore, their drawbacks are discussed and possible methods for their improvements are proposed. In contrast to black/gray-box controllers, a physics-based model can leverage the inherent dynamics of the system and facilitate implementation of special control techniques, which can optimize a specific performance criterion while meeting stringent system constraints. Thus, we present model-based controllers for the upper extremity rehabilitation robot using our developed musculoskeletal models. Two types of model-based controllers (i.e., nonlinear model predictive control using external 3-dimensional musculoskeletal model or internal 2-dimensional musculoskeletal model) are proposed. Their performances are evaluated in simulations and/or experiments. The biomechanically-plausible nonlinear model predictive control using internal 2-dimensional musculoskeletal model predicts muscular activities of the human subject and provides optimal assistance in real-time experiments, thereby conforming to our final goal for this project

Numerical computation and avoidance of manipulator singularities

This thesis develops general solutions to two open problems of robot kinematics: the exhaustive computation of the singularity set of a manipulator, and the synthesis of singularity-free paths between given configurations. Obtaining proper solutions to these problems is crucial, because singularities generally pose problems to the normal operation of a robot and, thus, they should be taken into account before the actual construction of a prototype. The ability to compute the whole singularity set also provides rich information on the global motion capabilities of a manipulator. The projections onto the task and joint spaces delimit the working regions in such spaces, may inform on the various assembly modes of the manipulator, and highlight areas where control or dexterity losses can arise, among other anomalous behaviour. These projections also supply a fair view of the feasible movements of the system, but do not reveal all possible singularity-free motions. Automatic motion planners allowing to circumvent problematic singularities should thus be devised to assist the design and programming stages of a manipulator. The key role played by singular configurations has been thoroughly known for several years, but existing methods for singularity computation or avoidance still concentrate on specific classes of manipulators. The absence of methods able to tackle these problems on a sufficiently large class of manipulators is problematic because it hinders the analysis of more complex manipulators or the development of new robot topologies. A main reason for this absence has been the lack of computational tools suitable to the underlying mathematics that such problems conceal. However, recent advances in the field of numerical methods for polynomial system solving now permit to confront these issues with a very general intention in mind. The purpose of this thesis is to take advantage of this progress and to propose general robust methods for the computation and avoidance of singularities on non-redundant manipulators of arbitrary architecture. Overall, the work seeks to contribute to the general understanding on how the motions of complex multibody systems can be predicted, planned, or controlled in an efficient and reliable way.Aquesta tesi desenvolupa solucions generals per dos problemes oberts de la cinemàtica de robots: el càlcul exhaustiu del conjunt singular d'un manipulador, i la síntesi de camins lliures de singularitats entre configuracions donades. Obtenir solucions adequades per aquests problemes és crucial, ja que les singularitats plantegen problemes al funcionament normal del robot i, per tant, haurien de ser completament identificades abans de la construcció d'un prototipus. La habilitat de computar tot el conjunt singular també proporciona informació rica sobre les capacitats globals de moviment d'un manipulador. Les projeccions cap a l'espai de tasques o d'articulacions delimiten les regions de treball en aquests espais, poden informar sobre les diferents maneres de muntar el manipulador, i remarquen les àrees on poden sorgir pèrdues de control o destresa, entre d'altres comportaments anòmals. Aquestes projeccions també proporcionen una imatge fidel dels moviments factibles del sistema, però no revelen tots els possibles moviments lliures de singularitats. Planificadors de moviment automàtics que permetin evitar les singularitats problemàtiques haurien de ser ideats per tal d'assistir les etapes de disseny i programació d'un manipulador. El paper clau que juguen les configuracions singulars ha estat àmpliament conegut durant anys, però els mètodes existents pel càlcul o evitació de singularitats encara es concentren en classes específiques de manipuladors. L'absència de mètodes capaços de tractar aquests problemes en una classe suficientment gran de manipuladors és problemàtica, ja que dificulta l'anàlisi de manipuladors més complexes o el desenvolupament de noves topologies de robots. Una raó principal d'aquesta absència ha estat la manca d'eines computacionals adequades a les matemàtiques subjacents que aquests problemes amaguen. No obstant, avenços recents en el camp de mètodes numèrics per la solució de sistemes polinòmics permeten ara enfrontar-se a aquests temes amb una intenció molt general en ment. El propòsit d'aquesta tesi és aprofitar aquest progrés i proposar mètodes robustos i generals pel càlcul i evitació de singularitats per manipuladors no redundants d'arquitectura arbitrària. En global, el treball busca contribuir a la comprensió general sobre com els moviments de sistemes multicos complexos es poden predir, planificar o controlar d'una manera eficient i segur

Hybrid Analog-Digital Co-Processing for Scientific Computation

In the past 10 years computer architecture research has moved to more heterogeneity and less adherence to conventional abstractions. Scientists and engineers hold an unshakable belief that computing holds keys to unlocking humanity's Grand Challenges. Acting on that belief they have looked deeper into computer architecture to find specialized support for their applications. Likewise, computer architects have looked deeper into circuits and devices in search of untapped performance and efficiency. The lines between computer architecture layers---applications, algorithms, architectures, microarchitectures, circuits and devices---have blurred. Against this backdrop, a menagerie of computer architectures are on the horizon, ones that forgo basic assumptions about computer hardware, and require new thinking of how such hardware supports problems and algorithms. This thesis is about revisiting hybrid analog-digital computing in support of diverse modern workloads. Hybrid computing had extensive applications in early computing history, and has been revisited for small-scale applications in embedded systems. But architectural support for using hybrid computing in modern workloads, at scale and with high accuracy solutions, has been lacking. I demonstrate solving a variety of scientific computing problems, including stochastic ODEs, partial differential equations, linear algebra, and nonlinear systems of equations, as case studies in hybrid computing. I solve these problems on a system of multiple prototype analog accelerator chips built by a team at Columbia University. On that team I made contributions toward programming the chips, building the digital interface, and validating the chips' functionality. The analog accelerator chip is intended for use in conjunction with a conventional digital host computer. The appeal and motivation for using an analog accelerator is efficiency and performance, but it comes with limitations in accuracy and problem sizes that we have to work around. The first problem is how to do problems in this unconventional computation model. Scientific computing phrases problems as differential equations and algebraic equations. Differential equations are a continuous view of the world, while algebraic equations are a discrete one. Prior work in analog computing mostly focused on differential equations; algebraic equations played a minor role in prior work in analog computing. The secret to using the analog accelerator to support modern workloads on conventional computers is that these two viewpoints are interchangeable. The algebraic equations that underlie most workloads can be solved as differential equations, and differential equations are naturally solvable in the analog accelerator chip. A hybrid analog-digital computer architecture can focus on solving linear and nonlinear algebra problems to support many workloads. The second problem is how to get accurate solutions using hybrid analog-digital computing. The reason that the analog computation model gives less accurate solutions is it gives up representing numbers as digital binary numbers, and instead uses the full range of analog voltage and current to represent real numbers. Prior work has established that encoding data in analog signals gives an energy efficiency advantage as long as the analog data precision is limited. While the analog accelerator alone may be useful for energy-constrained applications where inputs and outputs are imprecise, we are more interested in using analog in conjunction with digital for precise solutions. This thesis gives novel insight that the trick to do so is to solve nonlinear problems where low-precision guesses are useful for conventional digital algorithms. The third problem is how to solve large problems using hybrid analog-digital computing. The reason the analog computation model can't handle large problems is it gives up step-by-step discrete-time operation, instead allowing variables to evolve smoothly in continuous time. To make that happen the analog accelerator works by chaining hardware for mathematical operations end-to-end. During computation analog data flows through the hardware with no overheads in control logic and memory accesses. The downside is then the needed hardware size grows alongside problem sizes. While scientific computing researchers have for a long time split large problems into smaller subproblems to fit in digital computer constraints, this thesis is a first attempt to consider these divide-and-conquer algorithms as an essential tool in using the analog model of computation. As we enter the post-Moore’s law era of computing, unconventional architectures will offer specialized models of computation that uniquely support specific problem types. Two prominent examples are deep neural networks and quantum computers. Recent trends in computer science research show these unconventional architectures will soon have broad adoption. In this thesis I show another specialized, unconventional architecture is to use analog accelerators to solve problems in scientific computing. Computer architecture researchers will discover other important models of computation in the future. This thesis is an example of the discovery process, implementation, and evaluation of how an unconventional architecture supports specialized workloads

Probabilistic Framework for Sensor Management

A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions

Kinodynamic planning and control of closed-chain robotic systems

Aplicat embargament des de la data de defensa fins el dia 1/6/2022This work proposes a methodology for kinodynamic planning and trajectory control in robots with closed kinematic chains. The ability to plan trajectories is key in a robotic system, as it provides a means to convert high-level task commands¾like “move to that location'', or “throw the object at such a speed''¾into low-level controls to be followed by the actuators. In contrast to purely kinematic planners, which only generate collision-free paths in configuration space, kinodynamic planners compute state-space trajectories that also account for the dynamics and force limits of the robot. In doing so, the resulting motions are more realistic and exploit gravity, inertia, and centripetal forces to the benefit of the task. Existing kinodynamic planners are fairly general and can deal with complex problems, but they require the state coordinates to be independent. Therefore, they are hard to apply to robots with loop-closure constraints whose state space is not globally parameterizable. These constraints define a nonlinear manifold on which the trajectories must be confined, and they appear in many systems, like parallel robots, cooperative arms manipulating an object, or systems that keep multiple contacts with the environment. In this work, we propose three steps to generate optimal trajectories for such systems. In a first step, we determine a trajectory that avoids the collisions with obstacles and satisfies all kinodynamic constraints of the robot, including loop-closure constraints, the equations of motion, or any limits on the velocities or on the motor and constraint forces. This is achieved with a sampling-based planner that constructs local charts of the state space numerically, and with an efficient steering method based on linear quadratic regulators. In a second step, the trajectory is optimized according to a cost function of interest. To this end we introduce two new collocation methods for trajectory optimization. While current methods easily violate the kinematic constraints, those we propose satisfy these constraints along the obtained trajectories. During the execution of a task, however, the trajectory may be affected by unforeseen disturbances or model errors. That is why, in a third step, we propose two trajectory control methods for closed-chain robots. The first method enjoys global stability, but it can only control trajectories that avoid forward singularities. The second method, in contrast, has local stability, but allows these singularities to be traversed robustly. The combination of these three steps expands the range of systems in which motion planning can be successfully applied.Aquest treball proposa una metodologia per a la planificació cinetodinàmica i el control de trajectòries en robots amb cadenes cinemàtiques tancades. La capacitat de planificar trajectòries és clau en un robot, ja que permet traduir instruccions d'alt nivell com ara ¿mou-te cap aquella posició'' o ¿llença l'objecte amb aquesta velocitat'' en senyals de referència que puguin ser seguits pels actuadors. En comparació amb els planificadors purament cinemàtics, que només generen camins lliures de col·lisions a l'espai de configuracions, els planificadors cinetodinàmics obtenen trajectòries a l'espai d'estats que són compatibles amb les restriccions dinàmiques i els límits de força del robot. Els moviments que en resulten són més realistes i aprofiten la gravetat, la inèrcia i les forces centrípetes en benefici de la tasca que es vol realitzar. Els planificadors cinetodinàmics actuals són força generals i poden resoldre problemes complexos, però assumeixen que les coordenades d'estat són independents. Per tant, no es poden aplicar a robots amb restriccions de clausura cinemàtica en els quals l'espai d'estats no admeti una parametrització global. Aquestes restriccions defineixen una varietat diferencial sobre la qual cal mantenir les trajectòries, i apareixen en sistemes com ara els robots paral·lels, els braços que manipulen objectes coordinadament o els sistemes amb extremitats en contacte amb l'entorn. En aquest treball, proposem tres passos per generar trajectòries òptimes per a aquests sistemes. En un primer pas, determinem una trajectòria que evita les col·lisions amb els obstacles i satisfà totes les restriccions cinetodinàmiques, incloses les de clausura cinemàtica, les equacions del moviment o els límits en les velocitats i en les forces d'actuació o d'enllaç. Això s'aconsegueix mitjançant un planificador basat en mostratge aleatori que utilitza cartes locals construïdes numèricament, i amb un mètode eficient de navegació local basat en reguladors quadràtics lineals. En un segon pas, la trajectòria s'optimitza segons una funció de cost donada. A tal efecte, introduïm dos nous mètodes de col·locació per a l'optimització de trajectòries. Mentre els mètodes existents violen fàcilment les restriccions cinemàtiques, els que proposem satisfan aquestes restriccions al llarg de les trajectòries obtingudes. Durant l'execució de la tasca, tanmateix, la trajectòria pot veure's afectada per pertorbacions imprevistes o per errors deguts a incerteses en el model dinàmic. És per això que, en un tercer pas, proposem dos mètodes de control de trajectòries per robots amb cadenes tancades. El primer mètode gaudeix d'estabilitat global, però només permet controlar trajectòries que no travessin singularitats directes del robot. El segon mètode, en canvi, té estabilitat local, però permet travessar aquestes singularitats de manera robusta. La combinació d'aquests tres passos amplia el ventall de sistemes en els quals es pot aplicar amb èxit la planificació cinetodinàmica.Postprint (published version

Proceedings of the 3rd Annual Conference on Aerospace Computational Control, volume 1

Conference topics included definition of tool requirements, advanced multibody component representation descriptions, model reduction, parallel computation, real time simulation, control design and analysis software, user interface issues, testing and verification, and applications to spacecraft, robotics, and aircraft