From Persephone to Pan: D. H. Lawrence's mythopoeic vision of the integrated personality with special emphasis on the short fiction and other writings in the early nineteen twenties

This doctoral thesis was published in printed form in 1987. It was digitized from paper copy in 2013. Unfortunately on some pages the digitizaion process has not been complete, i.e there are some minor typographic erros on some pages.

Dynamic optimization for the trajectory planning of robot manipulators in the presence of obstacles

This paper presents an approach to the solution of moving a robot manipulator with minimum cost along a specified geometric path in the presence of obstacles. The main idea is to express obstacle avoidance in terms of the distances between potentially colliding parts. The optimal traveling time and the minimum mechanical energy of the actuators are considered together to build a multiobjective function. A simple numerical example involving a Cartesian manipulator arm with two-degree-of-freedom is described.

Modeling, optimizing and simulating robot calibration with accuracy improvement

This work describes techniques for modeling, optimizing and simulating calibration processes of robots using off-line programming. The identification of geometric parameters of the nominal kinematic model is optimized using techniques of numerical optimization of the mathematical model. The simulation of the actual robot and the measurement system is achieved by introducing random errors representing their physical behavior and its statistical repeatability. An evaluation of the corrected nominal kinematic model brings about a clear perception of the influence of distinct variables involved in the process for a suitable planning, and indicates a considerable accuracy improvement when the optimized model is compared to the non-optimized one.

Control of a one-legged robot with energy savings

This paper presents a new strategy to control an one-legged robot aiming to reduce the energy expended by the system. To validate this algorithm, a classic method as benchmark was used. This method has been extensively validated by simulations and experimental prototypes in the literature. For simplicity reasons, the work is restricted to the two dimensional case due to simplicity reasons. This new method is compared to the classic one with respect to performance and energy expended by the system. The model consists on a springy leg, a simple body, and an actuated hinge-type hip. The new control strategy is composed of three parts, considering the hopping height, the forward speed, and the body orientation separately. The method exploits the system passive dynamics, defined as non-forced response of the system. In this case, the model is modified adding a spring to the hip. The method defines a desired leg trajectory close to the passive hip swing movement. Simulation results for both methods are analyzed and compared.

Speed Control of an Autonomous Mobile Robot: Comparison between a PID Control and a Control Using Fuzzy Logic

An Autonomous Mobile Robot battery driven, with two traction wheels and a steering wheel is being developed. This Robot central control is regulated by an IPC, which controls every function of security, steering, positioning localization and driving. Each traction wheel is operated by a DC motor with independent control system. This system is made up of a chopper, an encoder and a microcomputer. The IPC transmits the velocity values and acceleration ramp references to the PIC microcontrollers. As each traction wheel control is independent, it's possible to obtain different speed values for each wheel. This process facilities the direction and drive changes. Two different strategies for speed velocity control were implemented; one works with PID, and the other with fuzzy logic. There were no changes in circuits and feedback control, except for the PIC microcontroller software. Comparing the two different speed control strategies the results were equivalent. However, in relation to the development and implementation of these strategies, the difficulties were bigger to implement the PID control.

A Test Bed Applied Mobile Robot Navigation

It is presented a test bed applied to studies on dynamics, control, and navigation of mobile robots. A cargo ship scale model was chosen, which can be radio-controlled or operated autonomously through an embedded control system. A control program, which manages on board mission execution, is implemented on a microcontroller. Navigation is based on an electronic compass, which includes automatic compensation for pitch and roll motions. Heading control loop is based on this sensor, and on a rudder positioning system. A propulsion control system is also implemented. Typical manoeuvres as the turning test and "zig-zag", were implemented and tested. They are included on a manoeuvre library, and can be accessed independently or in combined modes. The embedded system is also in charge of signal acquisition and storing during the missions. It is possible to analyse experiments on identification of ship dynamics, control, and navigation, through the data transferred to a PC by serial communication. Navigation is going to be improved by including inertial sensors on board, and a DGPS. Preliminary tests are aimed to ship identification, and manoeuvrability, using free model tests. Future steps include extending this system for developing other mobile robots as, ROVs, AUVs, and aerial vehicles.

Performance evaluation of 3D computer vision techniques

This work presents the implementation and comparison of three different techniques of three-dimensional computer vision as follows: • Stereo vision - correlation between two 2D images • Sensorial fusion - use of different sensors: camera 2D + ultrasound sensor (1D); • Structured light The computer vision techniques herein presented took into consideration the following characteristics: • Computational effort ( elapsed time for obtain the 3D information); • Influence of environmental conditions (noise due to a non uniform lighting, overlighting and shades); • The cost of the infrastructure for each technique; • Analysis of uncertainties, precision and accuracy. The option of using the Matlab software, version 5.1, for algorithm implementation of the three techniques was due to the simplicity of their commands, programming and debugging. Besides, this software is well known and used by the academic community, allowing the results of this work to be obtained and verified. Examples of three-dimensional vision applied to robotic assembling tasks ("pick-and-place") are presented.

Experimental study applied to an industrial robot by using variable structure controllers and friction compensation

Control of an industrial robot is mainly a problem of dynamics. It includes non-linearities, uncertainties and external perturbations that should be considered in the design of control laws. In this work, two control strategies based on variable structure controllers (VSC) and a PD control algorithm are compared in relation to the tracking errors considering friction. The controller's performances are evaluated by adding an static friction model. Simulations and experimental results show it is possible to diminish tracking errors by using a model based friction compensation scheme. A SCARA robot is used to illustrate the conclusions of this paper.

Machine vision methods for process measurements in pulping

The papermaking industry has been continuously developing intelligent solutions to characterize the raw materials it uses, to control the manufacturing process in a robust way, and to guarantee the desired quality of the end product. Based on the much improved imaging techniques and image-based analysis methods, it has become possible to look inside the manufacturing pipeline and propose more effective alternatives to human expertise. This study is focused on the development of image analyses methods for the pulping process of papermaking. Pulping starts with wood disintegration and forming the fiber suspension that is subsequently bleached, mixed with additives and chemicals, and finally dried and shipped to the papermaking mills. At each stage of the process it is important to analyze the properties of the raw material to guarantee the product quality. In order to evaluate properties of fibers, the main component of the pulp suspension, a framework for fiber characterization based on microscopic images is proposed in this thesis as the first contribution. The framework allows computation of fiber length and curl index correlating well with the ground truth values. The bubble detection method, the second contribution, was developed in order to estimate the gas volume at the delignification stage of the pulping process based on high-resolution in-line imaging. The gas volume was estimated accurately and the solution enabled just-in-time process termination whereas the accurate estimation of bubble size categories still remained challenging. As the third contribution of the study, optical flow computation was studied and the methods were successfully applied to pulp flow velocity estimation based on double-exposed images. Finally, a framework for classifying dirt particles in dried pulp sheets, including the semisynthetic ground truth generation, feature selection, and performance comparison of the state-of-the-art classification techniques, was proposed as the fourth contribution. The framework was successfully tested on the semisynthetic and real-world pulp sheet images. These four contributions assist in developing an integrated factory-level vision-based process control.

Weed mapping using a machine vision system

Weed mapping is a useful tool for site-specific herbicide applications. The objectives of this study were (1) to determine the percentage of land area covered by weeds in no-till and conventionally tilled fields of common bean using digital image processing and geostatistics, and (2) to compare two types of cameras. Two digital cameras (color and infrared) and a differential GPS were affixed to a center pivot structure for image acquisition. Sample field images were acquired in a regular grid pattern, and the images were processed to estimate the percentage of weed cover. After calculating the georeferenced weed percentage values, maps were constructed using geostatistical techniques. Based on the results, color images are recommended for mapping the percentage of weed cover in no-till systems, while infrared images are recommended for weed mapping in conventional tillage systems.

Flexible multibody dynamics and intelligent control of a hydraulically driven hybrid redundant robot machine

The assembly and maintenance of the International Thermonuclear Experimental Reactor (ITER) vacuum vessel (VV) is highly challenging since the tasks performed by the robot involve welding, material handling, and machine cutting from inside the VV. The VV is made of stainless steel, which has poor machinability and tends to work harden very rapidly, and all the machining operations need to be carried out from inside of the ITER VV. A general industrial robot cannot be used due to its poor stiffness in the heavy duty machining process, and this will cause many problems, such as poor surface quality, tool damage, low accuracy. Therefore, one of the most suitable options should be a light weight mobile robot which is able to move around inside of the VV and perform different machining tasks by replacing different cutting tools. Reducing the mass of the robot manipulators offers many advantages: reduced material costs, reduced power consumption, the possibility of using smaller actuators, and a higher payload-to-robot weight ratio. Offsetting these advantages, the lighter weight robot is more flexible, which makes it more difficult to control. To achieve good machining surface quality, the tracking of the end effector must be accurate, and an accurate model for a more flexible robot must be constructed. This thesis studies the dynamics and control of a 10 degree-of-freedom (DOF) redundant hybrid robot (4-DOF serial mechanism and 6-DOF 6-UPS hexapod parallel mechanisms) hydraulically driven with flexible rods under the influence of machining forces. Firstly, the flexibility of the bodies is described using the floating frame of reference method (FFRF). A finite element model (FEM) provided the Craig-Bampton (CB) modes needed for the FFRF. A dynamic model of the system of six closed loop mechanisms was assembled using the constrained Lagrange equations and the Lagrange multiplier method. Subsequently, the reaction forces between the parallel and serial parts were used to study the dynamics of the serial robot. A PID control based on position predictions was implemented independently to control the hydraulic cylinders of the robot. Secondly, in machining, to achieve greater end effector trajectory tracking accuracy for surface quality, a robust control of the actuators for the flexible link has to be deduced. This thesis investigates the intelligent control of a hydraulically driven parallel robot part based on the dynamic model and two schemes of intelligent control for a hydraulically driven parallel mechanism based on the dynamic model: (1) a fuzzy-PID self-tuning controller composed of the conventional PID control and with fuzzy logic, and (2) adaptive neuro-fuzzy inference system-PID (ANFIS-PID) self-tuning of the gains of the PID controller, which are implemented independently to control each hydraulic cylinder of the parallel mechanism based on rod length predictions. The serial component of the hybrid robot can be analyzed using the equilibrium of reaction forces at the universal joint connections of the hexa-element. To achieve precise positional control of the end effector for maximum precision machining, the hydraulic cylinder should be controlled to hold the hexa-element. Thirdly, a finite element approach of multibody systems using the Special Euclidean group SE(3) framework is presented for a parallel mechanism with flexible piston rods under the influence of machining forces. The flexibility of the bodies is described using the nonlinear interpolation method with an exponential map. The equations of motion take the form of a differential algebraic equation on a Lie group, which is solved using a Lie group time integration scheme. The method relies on the local description of motions, so that it provides a singularity-free formulation, and no parameterization of the nodal variables needs to be introduced. The flexible slider constraint is formulated using a Lie group and used for modeling a flexible rod sliding inside a cylinder. The dynamic model of the system of six closed loop mechanisms was assembled using Hamilton’s principle and the Lagrange multiplier method. A linearized hydraulic control system based on rod length predictions was implemented independently to control the hydraulic cylinders. Consequently, the results of the simulations demonstrating the behavior of the robot machine are presented for each case study. In conclusion, this thesis studies the dynamic analysis of a special hybrid (serialparallel) robot for the above-mentioned special task involving the ITER and investigates different control algorithms that can significantly improve machining performance. These analyses and results provide valuable insight into the design and control of the parallel robot with flexible rods.

Energy and Dynamics of the solar agricultural robot "SolarSprayer"

The main objective of the present study was to design an agricultural robot, which work is based on the generation of the electricity by the solar panel. To achieve the proper operation of the robot according to the assumed working cycle the detailed design of the main equipment was made. By analysing the possible areas of implementation together with developments, the economic forecast was held. As a result a decision about possibility of such device working in agricultural sector was made and the probable topics of the further study were found out.

Dual light barrier method for six degrees of freedom tool center point calibration of an industrial robot

Tool center point calibration is a known problem in industrial robotics. The major focus of academic research is to enhance the accuracy and repeatability of next generation robots. However, operators of currently available robots are working within the limits of the robot´s repeatability and require calibration methods suitable for these basic applications. This study was conducted in association with Stresstech Oy, which provides solutions for manufacturing quality control. Their sensor, based on the Barkhausen noise effect, requires accurate positioning. The accuracy requirement admits a tool center point calibration problem if measurements are executed with an industrial robot. Multiple possibilities are available in the market for automatic tool center point calibration. Manufacturers provide customized calibrators to most robot types and tools. With the handmade sensors and multiple robot types that Stresstech uses, this would require great deal of labor. This thesis introduces a calibration method that is suitable for all robots which have two digital input ports free. It functions with the traditional method of using a light barrier to detect the tool in the robot coordinate system. However, this method utilizes two parallel light barriers to simultaneously measure and detect the center axis of the tool. Rotations about two axes are defined with the center axis. The last rotation about the Z-axis is calculated for tools that have different width of X- and Y-axes. The results indicate that this method is suitable for calibrating the geometric tool center point of a Barkhausen noise sensor. In the repeatability tests, a standard deviation inside robot repeatability was acquired. The Barkhausen noise signal was also evaluated after recalibration and the results indicate correct calibration. However, future studies should be conducted using a more accurate manipulator, since the method employs the robot itself as a measuring device.

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.