Complex dynamics in the trajectory control of redundant manipulators

Redundant manipulators allow the trajectory optimization, the obstacle avoidance, and the resolution of singularities. For this type of manipulators, the kinematic control algorithms adopt generalized inverse matrices that may lead to unpredictable responses. Motivated by these problems this paper studies the complexity revealed by the trajectory planning scheme when controlling redundant manipulators. The results reveal fundamental properties of the chaotic phenomena and give a deeper insight towards the development of superior trajectory control algorithms.

Fractional dynamics in the trajectory control of redundant manipulators

Under the pseudoinverse control, robots with kinematical redundancy exhibit an undesirable chaotic joint motion which leads to an erratic behavior. This paper studies the complexity of fractional dynamics of the chaotic response. Fourier and wavelet analysis provides a deeper insight, helpful to know better the lack of repeatability problem of redundant manipulators. This perspective for the study of the chaotic phenomena will permit the development of superior trajectory control algorithms.

Chaotic Phenomena and Performance Optimization in the Trajectory Control of Redundant Manipulators

Redundant manipulators have some advantages when compared with classical arms because they allow the trajectory optimization, both on the free space and on the presence of abstacles, and the resolution of singularities. For this type of manipulators, several kinetic algorithms adopt generalized inverse matrices. In this line of thought, the generalized inverse control scheme is tested through several experiments that reveal the difficulties that often arise. Motivated by theseproblems this paper presents a new method that ptimizes the manipulability through a least squre polynomialapproximation to determine the joints positions. Moreover, the article studies influence on the dynamics, when controlling redundant and hyper-redundant manipulators. The experiment confirm the superior performance of the proposed algorithm for redundant and hyper-redundant manipulators, revealing several fundamental properties of the chaotic phenomena, and gives a deeper insight towards the future development of superior trajectory control algorithms.

Minimum jerk trajectory control for rehabilitation and haptic applications

Smooth trajectories are essential for safe interaction in between human and a haptic interface. Different methods and strategies have been introduced to create such smooth trajectories. This paper studies the creation of human-like movements in haptic interfaces, based on the study of human arm motion. These motions are intended to retrain the upper limb movements of patients that lose manipulation functions following stroke. We present a model that uses higher degree polynomials to define a trajectory and control the robot arm to achieve minimum jerk movements. It also studies different methods that can be driven from polynomials to create more realistic human-like movements for therapeutic purposes.

Chaos Dynamics in the Trajectory Conjtrol of Redundant Manipulators

Nonlinear Dynamics, chaos, Control, and Their Applications to Engineering Sciences: Vol. 6 - Applications of nonlinear phenomena

Controle inteligente aplicado a uma mesa de coordenadas de dois graus de liberdade

This work presents the design and construction of an X-Y table of two degrees of freedom, as well as the development of a fuzzy system for its position and trajectory control. The table is composed of two bases that move perpendicularly to each other in the horizontal plane, and are driven by two DC motors. Base position is detected by position sensors attached to the motor axes. A data acquisition board performs the interface between a laptop and the plant. The fuzzy system algorithm was implemented in LabVIEW® programming environment that processes the sensors signals and determines the control variables values that drive the motors. Experimental results using position reference signals (step type signal) and straight and circular paths reference signals are presented to demonstrate the dynamic behavior of fuzzy system

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Trajectory and Force Control of a Direct Drive Arm

Using the MIT Serial Link Direct Drive Arm as the main experimental device, various issues in trajectory and force control of manipulators were studied in this thesis. Since accurate modeling is important for any controller, issues of estimating the dynamic model of a manipulator and its load were addressed first. Practical and effective algorithms were developed fro the Newton-Euler equations to estimate the inertial parameters of manipulator rigid-body loads and links. Load estimation was implemented both on PUMA 600 robot and on the MIT Serial Link Direct Drive Arm. With the link estimation algorithm, the inertial parameters of the direct drive arm were obtained. For both load and link estimation results, the estimated parameters are good models of the actual system for control purposes since torques and forces can be predicted accurately from these estimated parameters. The estimated model of the direct drive arm was them used to evaluate trajectory following performance by feedforward and computed torque control algorithms. The experimental evaluations showed that the dynamic compensation can greatly improve trajectory following accuracy. Various stability issues of force control were studied next. It was determined that there are two types of instability in force control. Dynamic instability, present in all of the previous force control algorithms discussed in this thesis, is caused by the interaction of a manipulator with a stiff environment. Kinematics instability is present only in the hybrid control algorithm of Raibert and Craig, and is caused by the interaction of the inertia matrix with the Jacobian inverse coordinate transformation in the feedback path. Several methods were suggested and demonstrated experimentally to solve these stability problems. The result of the stability analyses were then incorporated in implementing a stable force/position controller on the direct drive arm by the modified resolved acceleration method using both joint torque and wrist force sensor feedbacks.

Autonomous ship collision free trajectory navigation and control algorithms

A new autonomous ship collision free (ASCF) trajectory navigation and control system has been introduced with a new recursive navigation algorithm based on analytic geometry and convex set theory for ship collision free guidance. The underlying assumption is that the geometric information of ship environment is available in the form of a polygon shaped free space, which may be easily generated from a 2D image or plots relating to physical hazards or other constraints such as collision avoidance regulations. The navigation command is given as a heading command sequence based on generating a way point which falls within a small neighborhood of the current position, and the sequence of the way points along the trajectory are guaranteed to lie within a bounded obstacle free region using convex set theory. A neurofuzzy network predictor which in practice uses only observed input/output data generated by on board sensors or external sensors (or a sensor fusion algorithm), based on using rudder deflection angle for the control of ship heading angle, is utilised in the simulation of an ESSO 190000 dwt tanker model to demonstrate the effectiveness of the system.

A proposed neural control for the trajectory tracking of a nonholonomic mobile robot with disturbances

In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains disturbances. The KNC is a variable structure controller (VSC) based on the sliding mode control theory (SMC), and applied to compensate the kinematic disturbances. The TNC is a inertia-based controller constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, and bounded unknown disturbances. Stability analysis with basis on Lyapunov method and simulations results are provided to show the effectiveness of the proposed approach. © 2012 Springer-Verlag.

Motion control and real-time systems: an approach to trajectory rebuilding in non-deterministic networks

Motion control is a sub-field of automation, in which the position and/or velocity of machines are controlled using some type of device. In motion control the position, velocity, force, pressure, etc., profiles are designed in such a way that the different mechanical parts work as an harmonious whole in which a perfect synchronization must be achieved. The real-time exchange of information in the distributed system that is nowadays an industrial plant plays an important role in order to achieve always better performance, better effectiveness and better safety. The network for connecting field devices such as sensors, actuators, field controllers such as PLCs, regulators, drive controller etc., and man-machine interfaces is commonly called fieldbus. Since the motion transmission is now task of the communication system, and not more of kinematic chains as in the past, the communication protocol must assure that the desired profiles, and their properties, are correctly transmitted to the axes then reproduced or else the synchronization among the different parts is lost with all the resulting consequences. In this thesis, the problem of trajectory reconstruction in the case of an event-triggered communication system is faced. The most important feature that a real-time communication system must have is the preservation of the following temporal and spatial properties: absolute temporal consistency, relative temporal consistency, spatial consistency. Starting from the basic system composed by one master and one slave and passing through systems made up by many slaves and one master or many masters and one slave, the problems in the profile reconstruction and temporal properties preservation, and subsequently the synchronization of different profiles in network adopting an event-triggered communication system, have been shown. These networks are characterized by the fact that a common knowledge of the global time is not available. Therefore they are non-deterministic networks. Each topology is analyzed and the proposed solution based on phase-locked loops adopted for the basic master-slave case has been improved to face with the other configurations.

Contributions to trajectory prediction theory and its application to arrival management for air traffic control

La gestión del tráfico aéreo (Air Traffic Management, ATM) está experimentando un cambio de paradigma hacia las denominadas operaciones basadas trayectoria. Bajo dicho paradigma se modifica el papel de los controladores de tráfico aéreo desde una operativa basada su intervención táctica continuada hacia una labor de supervisión a más largo plazo. Esto se apoya en la creciente confianza en las soluciones aportadas por las herramientas automatizadas de soporte a la decisión más modernas. Para dar soporte a este concepto, se precisa una importante inversión para el desarrollo, junto con la adquisición de nuevos equipos en tierra y embarcados, que permitan la sincronización precisa de la visión de la trayectoria, basada en el intercambio de información entre ambos actores. Durante los últimos 30 a 40 años las aerolíneas han generado uno de los menores retornos de la inversión de entre todas las industrias. Sin beneficios tangibles, la industria aérea tiene dificultades para atraer el capital requerido para su modernización, lo que retrasa la implantación de dichas mejoras. Esta tesis tiene como objetivo responder a la pregunta de si las capacidades actualmente instaladas en las aeronaves comerciales se pueden aplicar para lograr la sincronización de la trayectoria con el nivel de calidad requerido. Además, se analiza en ella si, conjuntamente con mejoras en las herramientas de predicción trayectorias instaladas en tierra en para facilitar la gestión de las arribadas, dichas capacidades permiten obtener los beneficios esperados en el marco de las operaciones basadas en trayectoria. Esto podría proporcionar un incentivo para futuras actualizaciones de la aviónica que podrían llevar a mejoras adicionales. El concepto operacional propuesto en esta tesis tiene como objetivo permitir que los aviones sean pilotados de una manera consistente con las técnicas actuales de vuelo optimizado. Se permite a las aeronaves que desciendan en el denominado “modo de ángulo de descenso gestionado” (path-managed mode), que es el preferido por la mayoría de las compañías aéreas, debido a que conlleva un reducido consumo de combustible. El problema de este modo es que en él no se controla de forma activa el tiempo de llegada al punto de interés. En nuestro concepto operacional, la incertidumbre temporal se gestiona en mediante de la medición del tiempo en puntos estratégicamente escogidos a lo largo de la trayectoria de la aeronave, y permitiendo la modificación por el control de tierra de la velocidad de la aeronave. Aunque la base del concepto es la gestión de las ordenes de velocidad que se proporcionan al piloto, para ser capaces de operar con los niveles de equipamiento típicos actualmente, dicho concepto también constituye un marco en el que la aviónica más avanzada (por ejemplo, que permita el control por el FMS del tiempo de llegada) puede integrarse de forma natural, una vez que esta tecnología este instalada. Además de gestionar la incertidumbre temporal a través de la medición en múltiples puntos, se intenta reducir dicha incertidumbre al mínimo mediante la mejora de las herramienta de predicción de la trayectoria en tierra. En esta tesis se presenta una novedosa descomposición del proceso de predicción de trayectorias en dos etapas. Dicha descomposición permite integrar adecuadamente los datos de la trayectoria de referencia calculada por el Flight Management System (FMS), disponibles usando Futuro Sistema de Navegación Aérea (FANS), en el sistema de predicción de trayectorias en tierra. FANS es un equipo presente en los aviones comerciales de fuselaje ancho actualmente en la producción, e incluso algunos aviones de fuselaje estrecho pueden tener instalada avionica FANS. Además de informar automáticamente de la posición de la aeronave, FANS permite proporcionar (parte de) la trayectoria de referencia en poder de los FMS, pero la explotación de esta capacidad para la mejora de la predicción de trayectorias no se ha estudiado en profundidad en el pasado. La predicción en dos etapas proporciona una solución adecuada al problema de sincronización de trayectorias aire-tierra dado que permite la sincronización de las dimensiones controladas por el sistema de guiado utilizando la información de la trayectoria de referencia proporcionada mediante FANS, y también facilita la mejora en la predicción de las dimensiones abiertas restantes usado un modelo del guiado que explota los modelos meteorológicos mejorados disponibles en tierra. Este proceso de predicción de la trayectoria de dos etapas se aplicó a una muestra de 438 vuelos reales que realizaron un descenso continuo (sin intervención del controlador) con destino Melbourne. Dichos vuelos son de aeronaves del modelo Boeing 737-800, si bien la metodología descrita es extrapolable a otros tipos de aeronave. El método propuesto de predicción de trayectorias permite una mejora en la desviación estándar del error de la estimación del tiempo de llegada al punto de interés, que es un 30% menor que la que obtiene el FMS. Dicha trayectoria prevista mejorada se puede utilizar para establecer la secuencia de arribadas y para la asignación de las franjas horarias para cada aterrizaje (slots). Sobre la base del slot asignado, se determina un perfil de velocidades que permita cumplir con dicho slot con un impacto mínimo en la eficiencia del vuelo. En la tesis se propone un nuevo algoritmo que determina las velocidades requeridas sin necesidad de un proceso iterativo de búsqueda sobre el sistema de predicción de trayectorias. El algoritmo se basa en una parametrización inteligente del proceso de predicción de la trayectoria, que permite relacionar el tiempo estimado de llegada con una función polinómica. Resolviendo dicho polinomio para el tiempo de llegada deseado, se obtiene de forma natural el perfil de velocidades optimo para cumplir con dicho tiempo de llegada sin comprometer la eficiencia. El diseño de los sistemas de gestión de arribadas propuesto en esta tesis aprovecha la aviónica y los sistemas de comunicación instalados de un modo mucho más eficiente, proporcionando valor añadido para la industria. Por tanto, la solución es compatible con la transición hacia los sistemas de aviónica avanzados que están desarrollándose actualmente. Los beneficios que se obtengan a lo largo de dicha transición son un incentivo para inversiones subsiguientes en la aviónica y en los sistemas de control de tráfico en tierra. ABSTRACT Air traffic management (ATM) is undergoing a paradigm shift towards trajectory based operations where the role of an air traffic controller evolves from that of continuous intervention towards supervision, as decision making is improved based on increased confidence in the solutions provided by advanced automation. To support this concept, significant investment for the development and acquisition of new equipment is required on the ground as well as in the air, to facilitate the high degree of trajectory synchronisation and information exchange required. Over the past 30-40 years the airline industry has generated one of the lowest returns on invested capital among all industries. Without tangible benefits realised, the airline industry may find it difficult to attract the required investment capital and delay acquiring equipment needed to realise the concept of trajectory based operations. In response to these challenges facing the modernisation of ATM, this thesis aims to answer the question whether existing aircraft capabilities can be applied to achieve sufficient trajectory synchronisation and improvements to ground-based trajectory prediction in support of the arrival management process, to realise some of the benefits envisioned under trajectory based operations, and to provide an incentive for further avionics upgrades. The proposed operational concept aims to permit aircraft to operate in a manner consistent with current optimal aircraft operating techniques. It allows aircraft to descend in the fuel efficient path managed mode as preferred by a majority of airlines, with arrival time not actively controlled by the airborne automation. The temporal uncertainty is managed through metering at strategically chosen points along the aircraft’s trajectory with primary use of speed advisories. While the focus is on speed advisories to support all aircraft and different levels of equipage, the concept also constitutes a framework in which advanced avionics as airborne time-of-arrival control can be integrated once this technology is widely available. In addition to managing temporal uncertainty through metering at multiple points, this temporal uncertainty is minimised by improving the supporting trajectory prediction capability. A novel two-stage trajectory prediction process is presented to adequately integrate aircraft trajectory data available through Future Air Navigation Systems (FANS) into the ground-based trajectory predictor. FANS is standard equipment on any wide-body aircraft in production today, and some single-aisle aircraft are easily capable of being fitted with FANS. In addition to automatic position reporting, FANS provides the ability to provide (part of) the reference trajectory held by the aircraft’s Flight Management System (FMS), but this capability has yet been widely overlooked. The two-stage process provides a ‘best of both world’s’ solution to the air-ground synchronisation problem by synchronising with the FMS reference trajectory those dimensions controlled by the guidance mode, and improving on the prediction of the remaining open dimensions by exploiting the high resolution meteorological forecast available to a ground-based system. The two-stage trajectory prediction process was applied to a sample of 438 FANS-equipped Boeing 737-800 flights into Melbourne conducting a continuous descent free from ATC intervention, and can be extrapolated to other types of aircraft. Trajectories predicted through the two-stage approach provided estimated time of arrivals with a 30% reduction in standard deviation of the error compared to estimated time of arrival calculated by the FMS. This improved predicted trajectory can subsequently be used to set the sequence and allocate landing slots. Based on the allocated landing slot, the proposed system calculates a speed schedule for the aircraft to meet this landing slot at minimal flight efficiency impact. A novel algorithm is presented that determines this speed schedule without requiring an iterative process in which multiple calls to a trajectory predictor need to be made. The algorithm is based on parameterisation of the trajectory prediction process, allowing the estimate time of arrival to be represented by a polynomial function of the speed schedule, providing an analytical solution to the speed schedule required to meet a set arrival time. The arrival management solution proposed in this thesis leverages the use of existing avionics and communications systems resulting in new value for industry for current investment. The solution therefore supports a transition concept from mixed equipage towards advanced avionics currently under development. Benefits realised under this transition may provide an incentive for ongoing investment in avionics.

A ROS-based Workspace Control and Trajectory Planner for a seven degrees of freedom Robotic arm

In this Bachelor Thesis I want to provide readers with tools and scripts for the control of a 7DOF manipulator, backed up by some theory of Robotics and Computer Science, in order to better contextualize the work done. In practice, we will see most common software, and developing environments, used to cope with our task: these include ROS, along with visual simulation by VREP and RVIZ, and an almost "stand-alone" ROS extension called MoveIt!, a very complete programming interface for trajectory planning and obstacle avoidance. As we will better appreciate and understand in the introduction chapter, the capability of detecting collision objects through a camera sensor, and re-plan to the desired end-effector pose, are not enough. In fact, this work is implemented in a more complex system, where recognition of particular objects is needed. Through a package of ROS and customized scripts, a detailed procedure will be provided on how to distinguish a particular object, retrieve its reference frame with respect to a known one, and then allow navigation to that target. Together with technical details, the aim is also to report working scripts and a specific appendix (A) you can refer to, if desiring to put things together.

An optimal control tool for trajectory generation of autonomous drones

In the recent years, autonomous aerial vehicles gained large popularity in a variety of applications in the field of automation. To accomplish various and challenging tasks the capability of generating trajectories has assumed a key role. As higher performances are sought, traditional, flatness-based trajectory generation schemes present their limitations. In these approaches the highly nonlinear dynamics of the quadrotor is, indeed, neglected. Therefore, strategies based on optimal control principles turn out to be beneficial, since in the trajectory generation process they allow the control unit to best exploit the actual dynamics, and enable the drone to perform quite aggressive maneuvers. This dissertation is then concerned with the development of an optimal control technique to generate trajectories for autonomous drones. The algorithm adopted to this end is a second-order iterative method working directly in continuous-time, which, under proper initialization, guarantees quadratic convergence to a locally optimal trajectory. At each iteration a quadratic approximation of the cost functional is minimized and a decreasing direction is then obtained as a linear-affine control law, after solving a differential Riccati equation. The algorithm has been implemented and its effectiveness has been tested on the vectored-thrust dynamical model of a quadrotor in a realistic simulative setup.

Visual Feedforward Control in Human Locomotion During Avoidance of Obstacles that Change Size

The purpose of the current study was to understand how visual information about an ongoing change in obstacle size is used during obstacle avoidance for both lead and trail limbs. Participants were required to walk in a dark room and to step over an obstacle edged with a special tape visible in the dark. The obstacle's dimensions were manipulated one step before obstacle clearance by increasing or decreasing its size. Two increasing and two decreasing obstacle conditions were combined with seven control static conditions. Results showed that information about the obstacle's size was acquired and used to modulate trail limb trajectory, but had no effect on lead limb trajectory. The adaptive step was influenced by the time available to acquire and process visual information. In conclusion, visual information about obstacle size acquired during lead limb crossing was used in a feedforward manner to modulate trail limb trajectory.