Computer-Aided Geometry Modeling

Techniques in computer-aided geometry modeling and their application are addressed. Mathematical modeling, solid geometry models, management of geometric data, development of geometry standards, and interactive and graphic procedures are discussed. The applications include aeronautical and aerospace structures design, fluid flow modeling, and gas turbine design

Virtual reality based creation of concept model designs for CAD systems

This work introduces a novel method to overcome most of the drawbacks in traditional methods for creating design models. The main innovation is the use of virtual tools to simulate the natural physical environment in which freeform. Design models are created by experienced designers. Namely, the model is created in a virtual environment by carving a work piece with tools that simulate NC milling cutters. Algorithms have been developed to support the approach, in which the design model is created in a Virtual Reality (VR) environment and selection and manipulation of tools can be performed in the virtual space. The desianer\u27s hand movements generate the tool trajectories and they are obtained by recording the position and orientation of a hand mounted motion tracker. Swept volumes of virtual tools are generated from the geometry of the tool and its trajectories. Then Boolean operations are performed on the swept volumes and the initial virtual stock (work piece) to create the design model. Algorithms have been developed as a part of this work to integrate the VR environment with a commercial CAD/CAM system in order to demonstrate the practical applications of the research results. The integrated system provides a much more efficient and easy-to-implement process of freeform model creation than employed in current CAD/CAM software. It could prove to be the prototype for the next-generation CAD/CAM system

View generated database

This document represents the final report for the View Generated Database (VGD) project, NAS7-1066. It documents the work done on the project up to the point at which all project work was terminated due to lack of project funds. The VGD was to provide the capability to accurately represent any real-world object or scene as a computer model. Such models include both an accurate spatial/geometric representation of surfaces of the object or scene, as well as any surface detail present on the object. Applications of such models are numerous, including acquisition and maintenance of work models for tele-autonomous systems, generation of accurate 3-D geometric/photometric models for various 3-D vision systems, and graphical models for realistic rendering of 3-D scenes via computer graphics

ASCI visualization tool evaluation, Version 2.0

The charter of the ASCI Visualization Common Tools subgroup was to investigate and evaluate 3D scientific visualization tools. As part of that effort, a Tri-Lab evaluation effort was launched in February of 1996. The first step was to agree on a thoroughly documented list of 32 features against which all tool candidates would be evaluated. These evaluation criteria were both gleaned from a user survey and determined from informed extrapolation into the future, particularly as concerns the 3D nature and extremely large size of ASCI data sets. The second step was to winnow a field of 41 candidate tools down to 11. The selection principle was to be as inclusive as practical, retaining every tool that seemed to hold any promise of fulfilling all of ASCI`s visualization needs. These 11 tools were then closely investigated by volunteer evaluators distributed across LANL, LLNL, and SNL. This report contains the results of those evaluations, as well as a discussion of the evaluation philosophy and criteria

Controlling and Learning Constrained Motions for Manipulation in Contact

Many practical tasks in robotic systems involving contact interaction with the environment, such as cleaning windows, writing or grasping, are inherently constrained, in that both the task and the environment impose constraints on the robot’s motion. While constraints from manipulation motions in contact represent a challenge when modelling and controlling such robotic systems, they might also be an opportunity, if exploited for decomposing complex controllers into simpler ones that are easier to design, implement, test and even learn from data. Modelling such systems requires incorporating these constraints in the robot’s dynamic model. In this thesis, I define the class of Task-based Constraints (TbCs) and prove that the forward dynamic models of a constrained system obtained through the Projected Dynamics (PD) and the Operational Space Formulation (OSF) are equivalent. Establishing such equivalence required: reformulating the PD constraint inertia matrix, generalising all its previous distinct algebraic variations; and generalising the OSF to rank deficient constraint Jacobian matrices. This generalization allows us to numerically handle redundant constraints and singular configurations, without having to use different controllers in the vicinity of such configurations. Furthermore, I show that we can recover both operational space control with constraints and the hybrid position/force control in the operational space from a multiple Task-based Constraint abstraction. I then propose a control and trajectory tracking approach for wiping the train cab front panels, using a velocity controlled robotic manipulator and a force/torque sensor attached to its end-effector, without using any surface model or vision-based surface detection. The control strategy consists of a hybrid position/force controller, adapted from the Operational Space Formulation, that aligns the cleaning tool with the surface normal, maintaining a set- point normal force, while simultaneously moving along the surface. The trajectory tracking strategy consists of specifying and tracking a two dimensional path that, when projected onto the train surface, corresponds to the desired pattern of motion. An experiment with the Baxter robot to wipe a highly curved surface with both a spiral and a raster scan motion patterns validates the approach. I also implemented the same approach in a scaled robot prototype, specifically designed to wipe a 1/8 scaled version of a train cab front, using a raster scan pattern. Learning these type of control policies subject to constraints is a challenging problem. This thesis proposes a Constraint-aware Policy Learning (CaPL) method that solves the policy learning problem on redundant robots which execute a policy acting in the null-space of a constraint. This learning approach allows the generalization of learnt control policies across constraints that are unknown during the training phase. The CaPL method splits the combined problem of learning constraints and policies into: first estimating the constraint, and then estimating an unconstrained policy using the remaining degrees of freedom. For a linear parametrization, there is a closed-form solution for the problem of estimating constraints based on Singular Value Decomposition (SVD). In this thesis, I propose another closed-form solution for constraint estimation for the TbC case, which includes estimating the task component without affecting the norm of the constraint matrix, based on Generalized Singular Value Decomposition (GSVD). I also discuss a metric for comparing the similarity of estimated constraints, which is useful to pre-process the trajectories recorded in the demonstrations. An experiment consisting in: learning a wiping task from human demonstration on flat surfaces; and reproducing it on an unknown curved surface using a force/torque based controller, to achieve tool alignment, validates the CaPL method. Despite the differences between the training and validation scenarios, the learnt policy still provides the desired wiping motion