People use both their hands together cooperatively in many everyday activities. The modern computer interface fails to take advantage of this basic human ability, with the exception of the keyboard. However, the keyboard is limited in that it does not afford continuous spatial input. The computer mouse is perfectly suited for the point and click tasks that are the major method of manipulation within graphical user interfaces, but standard computers have a single mouse. A single mouse does not afford spatial coordination between the two hands within the graphical user interface. Although the advent of the Universal Serial Bus has made it possible to easily plug in many peripheral devices, including a second mouse, modern operating systems work on the assumption of a single spatial input stream. Thus, if a second mouse is plugged into a Macintosh computer, a Windows computer or a UNIX computer, the two mice control the same cursor. <br /><br /> Previous work in two-handed or bimanual interaction techniques has often followed the asymmetric interaction guidelines set out by Yves Guiard's Kinematic Chain Model. In asymmetric interaction, the hands are assigned different tasks, based on hand dominance. I show that there is an interesting class of desktop user interface tasks which can be classified as symmetric. A symmetric task is one in which the two hands contribute equally to the completion of a unified task. I show that dual-mouse symmetric interaction techniques outperform traditional single-mouse techniques as well as dual-mouse asymmetric techniques for these symmetric tasks. I also show that users prefer the symmetric interaction techniques for these naturally symmetric tasks.

This report presents optimal control methods integrated with hierarchical control framework to realize real-time collision-free optimal trajectories for motion control in kinematic chain manipulator (KCM) robot systems under dynamic environments. Recently, they have been increasingly used in applications where manipulators are required to interact with random objects and humans. As a result, more complex trajectory planning schemes are required. The main objective of this research is to develop new motion control strategies that can enable such robots to operate efficiently and optimally in such unknown and dynamic environments. Two direct optimal control methods: The direct collocation method and discrete mechanics for optimal control methods are investigated for solving the related constrained optimal control problem and the results are compared. Using the receding horizon control structure, open-loop sub-optimal trajectories are generated as real-time input to the controller as opposed to the predefined trajectory over the entire time duration. This, in essence, captures the dynamic nature of the obstacles. The closed-loop position controller is then engaged to span the robot end-effector along this desired optimal path by computing appropriate torque commands for the joint actuators. Employing a two-degree of freedom technique, collision-free trajectories and robot environment information are transmitted in real-time by the aid of a bidirectional connectionless datagram transfer. A hierarchical network control platform is designed to condition triggering of precedent activities between a dedicated machine computing the optimal trajectory and the real-time computer running a low-level controller. Experimental results on a 2-link planar robot are presented to validate the main ideas. Real-time implementation of collision-free workspace trajectory control is achieved for cases where obstacles are arbitrarily changing in the robot workspace.

People use both their hands together cooperatively in many everyday activities. The modern computer interface fails to take advantage of this basic human ability, with the exception of the keyboard. However, the keyboard is limited in that it does not afford continuous spatial input. The computer mouse is perfectly suited for the point and click tasks that are the major method of manipulation within graphical user interfaces, but standard computers have a single mouse. A single mouse does not afford spatial coordination between the two hands within the graphical user interface. Although the advent of the Universal Serial Bus has made it possible to easily plug in many peripheral devices, including a second mouse, modern operating systems work on the assumption of a single spatial input stream. Thus, if a second mouse is plugged into a Macintosh computer, a Windows computer or a UNIX computer, the two mice control the same cursor. <br /><br /> Previous work in two-handed or bimanual interaction techniques has often followed the asymmetric interaction guidelines set out by Yves Guiard's Kinematic Chain Model. In asymmetric interaction, the hands are assigned different tasks, based on hand dominance. I show that there is an interesting class of desktop user interface tasks which can be classified as symmetric. A symmetric task is one in which the two hands contribute equally to the completion of a unified task. I show that dual-mouse symmetric interaction techniques outperform traditional single-mouse techniques as well as dual-mouse asymmetric techniques for these symmetric tasks. I also show that users prefer the symmetric interaction techniques for these naturally symmetric tasks.

This report presents optimal control methods integrated with hierarchical control framework to realize real-time collision-free optimal trajectories for motion control in kinematic chain manipulator (KCM) robot systems under dynamic environments. Recently, they have been increasingly used in applications where manipulators are required to interact with random objects and humans. As a result, more complex trajectory planning schemes are required. The main objective of this research is to develop new motion control strategies that can enable such robots to operate efficiently and optimally in such unknown and dynamic environments. Two direct optimal control methods: The direct collocation method and discrete mechanics for optimal control methods are investigated for solving the related constrained optimal control problem and the results are compared. Using the receding horizon control structure, open-loop sub-optimal trajectories are generated as real-time input to the controller as opposed to the predefined trajectory over the entire time duration. This, in essence, captures the dynamic nature of the obstacles. The closed-loop position controller is then engaged to span the robot end-effector along this desired optimal path by computing appropriate torque commands for the joint actuators. Employing a two-degree of freedom technique, collision-free trajectories and robot environment information are transmitted in real-time by the aid of a bidirectional connectionless datagram transfer. A hierarchical network control platform is designed to condition triggering of precedent activities between a dedicated machine computing the optimal trajectory and the real-time computer running a low-level controller. Experimental results on a 2-link planar robot are presented to validate the main ideas. Real-time implementation of collision-free workspace trajectory control is achieved for cases where obstacles are arbitrarily changing in the robot workspace.

The main objective of this research is the development of a framework for the automatic generation of systems of kinematic and dynamic equations that are suitable for real-time applications. In particular, the efficient simulation of constrained multibody systems is addressed. When modelled with ideal joints, many mechanical systems of practical interest contain closed kinematic chains, or kinematic loops, and are most conveniently modelled using a set of generalized coordinates of cardinality exceeding the degrees-of-freedom of the system. Dependent generalized coordinates add nonlinear algebraic constraint equations to the ordinary differential equations of motion, thereby producing a set of differential-algebraic equations that may be difficult to solve in an efficient yet precise manner. Several methods have been proposed for simulating such systems in real time, including index reduction, model simplification, and constraint stabilization techniques. In this work, the equations of motion are formulated symbolically using linear graph theory. The embedding technique is applied to eliminate the Lagrange multipliers from the dynamic equations and obtain one ordinary differential equation for each independent acceleration. The theory of Gröbner bases is then used to triangularize the kinematic constraint equations, thereby producing recursively solvable systems for calculating the dependent generalized coordinates given values of the independent coordinates. For systems that can be fully triangularized, the kinematic constraints are always satisfied exactly and in a fixed amount of time. Where full triangularization is not possible, a block-triangular form can be obtained that still results in more efficient simulations than existing iterative and constraint stabilization techniques. The proposed approach is applied to the kinematic and dynamic simulation of several mechanical systems, including six-bar mechanisms, parallel robots, and two vehicle suspensions: a five-link and a double-wishbone. The efficient kinematic solution generated for the latter is used in the real-time simulation of a vehicle with double-wishbone suspensions on both axles, which is implemented in a hardware- and operator-in-the-loop driving simulator. The Gröbner basis approach is particularly suitable for situations requiring very efficient simulations of multibody systems whose parameters are constant, such as the plant models in model-predictive control strategies and the vehicle models in driving simulators.

The main objective of this research is the development of a framework for the automatic generation of systems of kinematic and dynamic equations that are suitable for real-time applications. In particular, the efficient simulation of constrained multibody systems is addressed. When modelled with ideal joints, many mechanical systems of practical interest contain closed kinematic chains, or kinematic loops, and are most conveniently modelled using a set of generalized coordinates of cardinality exceeding the degrees-of-freedom of the system. Dependent generalized coordinates add nonlinear algebraic constraint equations to the ordinary differential equations of motion, thereby producing a set of differential-algebraic equations that may be difficult to solve in an efficient yet precise manner. Several methods have been proposed for simulating such systems in real time, including index reduction, model simplification, and constraint stabilization techniques. In this work, the equations of motion are formulated symbolically using linear graph theory. The embedding technique is applied to eliminate the Lagrange multipliers from the dynamic equations and obtain one ordinary differential equation for each independent acceleration. The theory of Gröbner bases is then used to triangularize the kinematic constraint equations, thereby producing recursively solvable systems for calculating the dependent generalized coordinates given values of the independent coordinates. For systems that can be fully triangularized, the kinematic constraints are always satisfied exactly and in a fixed amount of time. Where full triangularization is not possible, a block-triangular form can be obtained that still results in more efficient simulations than existing iterative and constraint stabilization techniques. The proposed approach is applied to the kinematic and dynamic simulation of several mechanical systems, including six-bar mechanisms, parallel robots, and two vehicle suspensions: a five-link and a double-wishbone. The efficient kinematic solution generated for the latter is used in the real-time simulation of a vehicle with double-wishbone suspensions on both axles, which is implemented in a hardware- and operator-in-the-loop driving simulator. The Gröbner basis approach is particularly suitable for situations requiring very efficient simulations of multibody systems whose parameters are constant, such as the plant models in model-predictive control strategies and the vehicle models in driving simulators.

This work presents a system for semi-autonomous optical localization of distant moving targets using multiple positionable cameras. The cameras were calibrated and stationed using custom designed calibration targets and methodology with the objective to alleviate the main sources of errors which were pinpointed in thorough precision analysis. The detection of the target is performed manually, while the visual tracking is automatic and it utilizes two state-of-the-art approaches. The estimation of the target location in 3-space is based on multi-view triangulation working with noisy measurements. A basic setup consisting of two camera units was tested against static targets and a moving terrestrial target, and the precision of the location estimation was compared to the theoretical model. The modularity and portability of the system allows fast deployment in a wide range of scenarios including perimeter monitoring or early threat detection in defense systems, as well as air traffic control in public space.

[ES] Uno de los elementos más importantes en el sistema de control de un robot es su Modelo Cinemático Inverso (IKM, por sus siglas en inglés), el cual calcula las referencias de posición y velocidad requeridas para que dicho robot pueda seguir una trayectoria. Los métodos más comúnmente empleados para la síntesis del IKM de sistemas robotizados de cadena cinemática abierta dependen fuertemente de la geometría del robot, por lo que no son procedimientos sistemáticos que puedan ser aplicados uniformemente en todas las situaciones. Este proyecto presenta el desarrollo de un procedimiento sistemático para la síntesis del IKM completo de sistemas robotizados no redundantes de cadena cinemática abierta usando la teoría de Bases de Groebner, el cual no depende de la geometría del robot. Las entradas del procedimiento desarrollado son los parámetros de Denavit-Hartenberg del robot y el rango de movimiento de sus actuadores, mientras que la salida es el IKM sintetizado, listo para ser usado en el sistema de control del robot o en una simulación de su funcionamiento. El desempeño del procedimiento desarrollado fue demostrado sintetizando los IKMs de un manipulador PUMA y un hexápodo caminante. Los tiempos de ejecución de ambos IKMs son comparables con los requeridos por los modelos cinemáticos calculados por procedimientos tradicionales, y los errores de las referencias que ofrecen como salida son totalmente despreciables. Los IKMs sintetizados son completos, porque no sólo ofrecen las referencias de posición para todos los actuadores del robot, sino que también calculan las correspondientes referencias de velocidades y aceleraciones de dichos actuadores, por lo que el procedimiento desarrollado puede ser empleado en una amplia variedad de sistemas robotizados. / [CA] Un dels elements més importants en el sistema de control d'un robot és el seu Model Cinemàtic Invers (IKM, per les seues sigles en anglés), el qual calcula les referències de posició i velocitat requerides perquè aquest robot puga seguir una trajectòria. Els mètodes més comunament emprats per a la síntesi del IKM de sistemes robotitzats de cadena cinemàtica oberta depenen fortament de la geometria del robot analitzat, per la qual cosa no són procediments sistemàtics que puguen ser aplicats uniformement en totes les situacions. Aquest projecte presenta el desenvolupament d'un procediment sistemàtic per a la síntesi del IKM complet de sistemes robotitzats no redundants de cadena cinemàtica oberta usant la teoria de Bases de Groebner, el qual no depén de la geometria del robot. Les entrades del procediment desenvolupat són els paràmetres de Denavit-Hartenberg del robot i el rang de moviment dels seus actuadors, mentre que l'eixida és el IKM sintetitzat, llest per a ser usat en el sistema de control del robot o en una simulació del seu funcionament. L'acompliment del procediment desenvolupat va ser demostrat sintetitzant els IKMs d'un manipulador PUMA i un robot caminante. Els temps d'execució de tots dos IKMs són comparables amb els requerits pels models cinemàtics calculats per procediments tradicionals, i els errors de les referències que ofereixen com a eixida són totalment menyspreables. Els IKMs sintetitzats són complets, perquè no sols ofereixen les referències de posició per a tots els actuadors del robot, sinó que també calculen les corresponents referències de velocitats i acceleracions d'aquests actuadors, per la qual cosa el procediment desenvolupat pot ser emprat en una àmplia varietat de sistemes robotitzats. / [EN] One of the most important elements of a robot's control system is its Inverse Kinematic Model (IKM), which calculates the position and velocity references required by the robot's actuators to follow a trajectory. The methods that are commonly used to synthesize the IKM of open-chain robotic systems strongly depend on the geometry of the analyzed robot, so they are not systematic procedures that can be applied equally in all situations. This project presents the development of a systematic procedure to synthesize the complete IKM of non-redundant open-chain robotic systems using Groebner Basis theory, which does not depend on the robot's geometry. The inputs to the developed procedure are the robot's Denavit-Hartenberg parameters and the movement range of its actuators, while the output is the IKM, ready to be used in the robot's control system or in a simulation of its behavior. This procedure's performance was proved synthesizing the IKMs of a PUMA manipulator and a walking hexapod robot. The computation times of both IKMs are comparable to those required by the kinematic models calculated by traditional methods, while the errors of their computed references were absolutely negligible. The synthesized IKMs are complete in the sense that they not only supply the position reference for all the robot's actuators, but also the corresponding references for their velocities and accelerations, so the developed procedure can be used in a wide range of robotic systems. / Guzmán Giménez, J. (2022). Synthesis of the Complete Inverse Kinematic Model of Non-Redundant Open-Chain Robotic Systems using Groebner Basis Theory [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181632 / TESIS