Improving robotic machining accuracy through experimental error investigation and modular compensation

Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials. This paper analyzes the sources of errors in robotic machining and characterizes them in amplitude and frequency. Experiments under different conditions represent a typical set of industrial applications and allow a qualified evaluation. Based on this analysis, a modular approach is proposed to overcome these obstacles, applied both during program generation (offline) and execution (online). Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high-dynamic compensation mechanism on piezo-actuator basis

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

Modelling and identification of a six axes industrial robot

This paper deals with the modelling and identification of a six axes industrial St ¨aubli RX90 robot. A non-linear finite element method is used to generate the dynamic equations of motion in a form suitable for both simulation and identification. The latter requires that the equations of motion are linear in the inertia parameters. Joint friction is described by a friction model that describes the friction behaviour in the full velocity range necessary for identification. Experimental parameter identification by means of linear least squares techniques showed to be very suited for identification of the unknown parameters, provided that the problem is properly scaled and that the influence of disturbances is sufficiently analysed and managed. An analysis of the least squares problem by means of a singular value decomposition is preferred as it not only solves the problem of rank deficiency, but it also can correctly deal with measurement noise and unmodelled dynamics

A quasi-static model-based control methodology for articulated mechanical systems

Hazardous environments encountered in nuclear clean-up tasks mandate the use of complex robotic systems in many situations. The operation of these systems is now performed primarily under teleoperation. This is, at best, five times slower than equivalent direct human contact operations.One way to increase remote work efficiency is to use automation for specific tasks. However, the unstructured, complex nature of the environment along with the inherent structural flexibility of mobile robot work systems makes task automation difficult and in meiny cases impossible.This research considers a quasi-static macroscopic modeling methodology that could be combined with sensor-guided manipulation schemes to achieve the needed operational accuracies for remote work task automation. Application of this methodology begins with an off-line analysis phase in which the system is identified in terms of the ideal D-H parameters and its structural elements. Themanipulator is modeled with fundamental components (i.e. beam elements, hydraulic elements, etc)and then analyzed to determine load dependent functions that predict deflections at each joint and the end of each link. Next, forces applied at the end-effector and gravity loads are projected into local link coordinates using the undeflected pose of the manipulator. These local loads are then used to calculate deflections which are expressed as 4 by 4 homogeneous transformations and inserted into the original manipulator transformations to predict end-effector position and orientation (anderror/deflection vector). The error/deflection vector is then used to determine corrective actions based on the manipulator flexibilities, pose and loading. This corrective action alters the manipulator commands such that the manipulator end-effector is moved to the desired location based on the error between the model predictions and commanded position using the ideal kinematics.The modeling methodology can readily be applied to any kinematic chain. This allows analysis of a conceptual system in terms of basic mechanics and structural deflections. The methodology allows components such as actuators or links to be interchanged in simulation so that alternative designs may be tested. This capability could help avoid potentially costly conceptual design flaws at a very early stage in the design process.Real-time compensation strategies have been developed so as to lessen concerns with structural deformation during use. The compensation strategies presented here show that the modeling methods can be used to increase the end-effector accuracy by calculating the deflections and command adjustments iteratively in real-time. The iterations show rapid convergence of the adjusted command positions to reach the desired end-effector location. The compensation methods discussed are easily altered to fit systems of any complexity, only requiring changes in the number of variables and the number of equations to solve. Most importantly, however, is that the modeling methodology,in conjunction with the compensation methods, can be used to correct for a significant fraction of the errors associated with manipulator flexibility effects. Implementation in a real-time system only involves changes in path planning, not in low-level control.The modeling methods and deflection predictions were verified using a sub-system of the OakRidge National Laboratory\u27s Dual Arm Work Platform. The experimental method used simple,non-contact measurement devices that are minimally intrusive to the manipulator\u27s workspace. The Results show good correlation between model and experimental results for some configurations. Experimental results can be extrapolated to predict that errors could be reduced from several inches to several tenths of an inch for systems like the Dual Arm Work Platform in some configurations.Continuing work will investigate applications to selective automation for Decontamination and Dismantlement tasks, using this work as a necessary foundation

The design and characterisation of miniature robotics for astronomical instruments

Micro robotics has the potential to improve the efficiency and reduce cost of future multi-object instruments for astronomy. This thesis reports on the development and evolution of a micro autonomous pick-off mirror called the Micro Autonomous Positioning System (MAPS) that can be used in a multi-object spectrograph. The design of these micro-autonomous pick-off mirrors is novel as they are capable of high precision positioning using electromagnetic propulsion through utilising non-conventional components and techniques. These devices are self-driven robotic units, which with the help of an external control system are capable of positioning themselves on an instruments focal plane to within 24 μm. This is different from other high precision micro robotics as they normally use piezoelectric actuators for propulsion. Micro robots have been developed that use electromagnetic motors, however they are not used for high precision applications. Although there is a plethora of literature covering design, functionality and capability of precision micro autonomous systems, there is limited research on characterisation methods for their use in astronomical applications. This work contributes not only to the science supporting the design of a micro-autonomous pick-off mirror but also presents a framework for characterising such miniature mechanisms. The majority of instruments are presented with a curved focal plane. Therefore, to ensure that the pick-off mirrors are aligned properly with the receiving optics, either the pick-off mirror needs to be tipped or the receiving optics repositioned. Currently this function is implemented in the beam steering mirror (i.e. the receiving optics). The travel range required by the beam steering mirror is relatively large, and as such, it is more difficult to achieve the positional accuracy and stability. By incorporating this functionality in the pick-off mirror, the instrument can be optimised in terms of size, accuracy and stability. A unique self-adjusting mirror (SAM) is thus proposed as a solution and detailed. As a proof-of-concepts both MAPS and SAM usability in multi-object spectrographs was evaluated and validated. The results indicate their potential to meet the requirements of astronomical instruments and reduce both the size and cost