Identification of robotic manipulators' inverse dynamics coefficients via model-based adaptive networks

The values of a given manipulator's dynamics coefficients need to be accurately identified in order to employ model-based algorithms in the control of its motion. This thesis details the development of a novel form of adaptive network which is capable of accurately learning the coefficients of systems, such as manipulator inverse dynamics, where the algebraic form is known but the coefficients' values are not. Empirical motion data from a pair of PUMA 560s has been processed by the Context-Sensitive Linear Combiner (CSLC) network developed, and the coefficients of their inverse dynamics identified. The resultant precision of control is shown to be superior to that achieved from employing dynamics coefficients derived from direct measurement. As part of the development of the CSLC network, the process of network learning is examined. This analysis reveals that current network architectures for processing analogue output systems with high input order are highly unlikely to produce solutions that are good estimates throughout the entire problem space. In contrast, the CSLC network is shown to generalise intrinsically as a result of its structure, whilst its training is greatly simplified by the presence of only one minima in the network's error hypersurface. Furthermore, a fine-tuning algorithm for network training is presented which takes advantage of the CSLC network's single adaptive layer structure and does not rely upon gradient descent of the network error hypersurface, which commonly slows the later stages of network training

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation

A generic computer simulation for manipulator systems (ROBSIM) was implemented and the specific technologies necessary to increase the role of automation in various missions were developed. The specific items developed are: (1) capability for definition of a manipulator system consisting of multiple arms, load objects, and an environment; (2) capability for kinematic analysis, requirements analysis, and response simulation of manipulator motion; (3) postprocessing options such as graphic replay of simulated motion and manipulator parameter plotting; (4) investigation and simulation of various control methods including manual force/torque and active compliances control; (5) evaluation and implementation of three obstacle avoidance methods; (6) video simulation and edge detection; and (7) software simulation validation

Tele-Autonomous control involving contact

Object localization and its application in tele-autonomous systems are studied. Two object localization algorithms are presented together with the methods of extracting several important types of object features. The first algorithm is based on line-segment to line-segment matching. Line range sensors are used to extract line-segment features from an object. The extracted features are matched to corresponding model features to compute the location of the object. The inputs of the second algorithm are not limited only to the line features. Featured points (point to point matching) and featured unit direction vectors (vector to vector matching) can also be used as the inputs of the algorithm, and there is no upper limit on the number of the features inputed. The algorithm will allow the use of redundant features to find a better solution. The algorithm uses dual number quaternions to represent the position and orientation of an object and uses the least squares optimization method to find an optimal solution for the object's location. The advantage of using this representation is that the method solves for the location estimation by minimizing a single cost function associated with the sum of the orientation and position errors and thus has a better performance on the estimation, both in accuracy and speed, than that of other similar algorithms. The difficulties when the operator is controlling a remote robot to perform manipulation tasks are also discussed. The main problems facing the operator are time delays on the signal transmission and the uncertainties of the remote environment. How object localization techniques can be used together with other techniques such as predictor display and time desynchronization to help to overcome these difficulties are then discussed

Identification of natural frequency components of articulated flexible structures

M.S.Wayne J. Boo

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

Exploração inteligente de objetos por manipulador robótico

The end goal of this dissertation is to develop an autonomous exploration robot that is capable of choosing the Next Best View which reveals the most amount of information about a given volume. The exploration solution is based on a robotic manipulator, a RGB-D sensor and ROS. The manipulator provides movement while the sensor evaluates the scene in its Field of View. Using an OcTree implementation to reconstruct the environment, the portions of the de ned exploration volume where no information has been gathered yet are segmented. This segmentation (or clustering) will help on the pose sampling operation in the sense that all generated poses are plausible. Ray casting is performed, either based on the sensor's resolution or the characteristics of the unknown scene, to assess the pose quality. The pose that is estimated to provide the evaluation of the highest amount of unknown space is the one chosen to be visited next, i.e., the Next Best View. The exploration reaches its end when all the unknown voxels have been evaluated or, those who were not, are not possible to be measured by any reachable pose. Two case studies are presented to test the performance and adaptability of this work. The developed system is able to explore a given scene which, initially, it has no information about. The solution provided is, not only, adaptable to changes in the environment during the exploration, but also, portable to other manipualtors rather than the one used in the development.O objetivo nal desta dissertação é desenvolver um robot de exploração autônomo capaz de escolher a Próxima Melhor Vista que revela a maior quantidade de informações sobre um determinado volume. A solução de exploração é baseada num manipulador robótico, num sensor RGB-D e em ROS. O manipulador proporciona movimento enquanto o sensor avalia a cena no seu campo de visão. Usando uma implementação Oc- Tree para reconstruir o ambiente, as partes do volume de exploração de nido onde nenhuma informação ainda foi recolhida são segmentadas. Esta segmenta ção (ou agrupamento) ajudará na operação de amostragem de poses no sentido em que todas as poses geradas são plausíveis. Ray casting é realizado, seja com base na resolução do sensor ou nas características da cena desconhecida, para avaliar a qualidade da pose. A pose que é estimado fornecer a avaliação da maior quantidade de espaço desconhecido é a escolhida para ser visitada em seguida, ou seja, a Próxima Melhor Vista. A exploração chega ao m quando todos os voxels desconhecidos tiverem sido avaliados ou, aqueles que não o foram, não sejam possíveis de serem medidos por qualquer pose alcançável. Dois casos de estudo são apresentados para testar o desempenho e adaptabilidade deste trabalho. O sistema desenvolvido é capaz de explorar uma determinada cena sobre a qual, inicialmente, não tem informação. A solução apresentada é, não só, adaptável às mudanças no ambiente durante a explora ção, mas também, portável para outros manipuladores que não o utilizado no desenvolvimento.Mestrado em Engenharia Mecânic

Kinematic Calibration of Parallel Kinematic Machines on the Example of the Hexapod of Simple Design

The aim of using parallel kinematic motion systems as an alternative of conventional machine tools for precision machining has raised the demands made on the accuracy of identification of the geometric parameters that are necessary for the kinematic transformation of the motion variables. The accuracy of a parallel manipulator is not only dependent upon an accurate control of its actuators but also upon a good knowledge of its geometrical characteristics. As the platform's controller determines the length of the actuators according to the nominal model, the resulted pose of the platform is inaccurate. One way to enhance platform accuracy is by kinematic calibration, a process by which the actual kinematic parameters are identified and then implemented to modify the kinematic model used by the controller. The first and most general valuation criterion for the actual calibration approaches is the relative improvement of the motion accuracy, eclipsing the other aspects to pay for it. The calibration outlay has been underestimated or even neglected for a long time. The scientific value of the calibration procedure is not only in direct proportion to the achieved accuracy, but also to the calibration effort. These demands become particularly stringent in case of the calibration of hexapods of the so-called simple design. The objectives of the here proposed new calibration procedure are based on the deficits mentioned above under the special requirements due to the circumstances of the simple design-concept. The main goals of the procedure can be summarized in obtaining the basics for an automated kinematic calibration procedure which works efficiently, quickly, effectively and possibly low-cost, all-in-one economically applied to the parallel kinematic machines. The problem will be approached systematically and taking step by step the necessary conclu-sions and measurements through: Systematical analysis of the workspace to determine the optimal measuring procedure, measurements with automated data acquisition and evaluation, simulated measurements based on the kinematic model of the structure and identifying the kinematic parameters using efficient optimization algorithms. The presented calibration has been successfully implemented and tested on the hexapod of simple design `Felix' available at the IWM, TU Dresden. The obtained results encourage the application of the procedure to other hexapod structures

Aspects of an open architecture robot controller and its integration with a stereo vision sensor.

The work presented in this thesis attempts to improve the performance of industrial robot systems in a flexible manufacturing environment by addressing a number of issues related to external sensory feedback and sensor integration, robot kinematic positioning accuracy, and robot dynamic control performance. To provide a powerful control algorithm environment and the support for external sensor integration, a transputer based open architecture robot controller is developed. It features high computational power, user accessibility at various robot control levels and external sensor integration capability. Additionally, an on-line trajectory adaptation scheme is devised and implemented in the open architecture robot controller, enabling a real-time trajectory alteration of robot motion to be achieved in response to external sensory feedback. An in depth discussion is presented on integrating a stereo vision sensor with the robot controller to perform external sensor guided robot operations. Key issues for such a vision based robot system are precise synchronisation between the vision system and the robot controller, and correct target position prediction to counteract the inherent time delay in image processing. These were successfully addressed in a demonstrator system based on a Puma robot. Efforts have also been made to improve the Puma robot kinematic and dynamic performance. A simple, effective, on-line algorithm is developed for solving the inverse kinematics problem of a calibrated industrial robot to improve robot positioning accuracy. On the dynamic control aspect, a robust adaptive robot tracking control algorithm is derived that has an improved performance compared to a conventional PID controller as well as exhibiting relatively modest computational complexity. Experiments have been carried out to validate the open architecture robot controller and demonstrate the performance of the inverse kinematics algorithm, the adaptive servo control algorithm, and the on-line trajectory generation. By integrating the open architecture robot controller with a stereo vision sensor system, robot visual guidance has been achieved with experimental results showing that the integrated system is capable of detecting, tracking and intercepting random objects moving in 3D trajectory at a velocity up to 40mm/s

Decision-making and problem-solving methods in automation technology

The state of the art in the automation of decision making and problem solving is reviewed. The information upon which the report is based was derived from literature searches, visits to university and government laboratories performing basic research in the area, and a 1980 Langley Research Center sponsored conferences on the subject. It is the contention of the authors that the technology in this area is being generated by research primarily in the three disciplines of Artificial Intelligence, Control Theory, and Operations Research. Under the assumption that the state of the art in decision making and problem solving is reflected in the problems being solved, specific problems and methods of their solution are often discussed to elucidate particular aspects of the subject. Synopses of the following major topic areas comprise most of the report: (1) detection and recognition; (2) planning; and scheduling; (3) learning; (4) theorem proving; (5) distributed systems; (6) knowledge bases; (7) search; (8) heuristics; and (9) evolutionary programming

Robot Calibration Using Artificial Neural Networks

Robot calibration is an integrated procedure of measurement and data processing to improve and maintain robot positioning accuracy. Existing robot calibration techniques require extensive human intervention and off-line processing, which preclude the techniques from being used to perform on-site calibration in an industrial environment at regular intervals. This thesis investigates and develops intelligent calibration processing algorithms and a novel measurement method toward rapid autonomous robot calibration in a shop-floor environment.Artificial Neural Network (ANN) techniques have been vigorously investigated for calibration data processing (modelling, identification and compensation). A new identification algorithm has been developed for estimating robot kinematic parameter errors using Hopfield continuous-valued type Recurrent Neural Network (RNN). The RNN-based algorithm is computationally more efficient and robust compared with conventional optimisation approaches.A generic accuracy model which accounts for various error sources was introduced. A higher-order neural network was used for implementation of the generic accuracy model. Due to the ANN learning capability, computational power and adaptability, the ANN-based accuracy representation offers an appealing solution to the complex modelling problem.Efficient and robust accuracy compensation algorithms have been developed under the framework of artificial neural networks. The ANN-based algorithms provide constant-time inverse compensation therefore are suitable for on-line implementation. Both path compensation and compensation near robot singularity were tackled using the new algorithm.A novel autonomous calibration tool was developed using a trigger probe and a constraint plane. The new method eliminates any use of external measuring devices to determine robot end-effector location measurements, enabling the robot to perform self-calibration on a production line. Robot accuracy was improved to the level of its repeatability within the local calibration volume using the new calibration scheme, which is consistent with the results from using a precision external measuring device, in this case a Coordinate Measuring Machine (CMM)