Active haptic exploration for 3D shape reconstruction.

by Fung Wai Keung.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 146-151).Acknowledgements --- p.viiiAbstract --- p.1Chapter 1 --- Overview --- p.3Chapter 1.1 --- Tactile Sensing in Human and Robot --- p.4Chapter 1.1.1 --- Human Hands and Robotic Hands --- p.4Chapter 1.1.2 --- Mechanoreceptors in skin and Tactile Sensor Arrays --- p.7Chapter 1.2 --- Motivation --- p.12Chapter 1.3 --- Objectives --- p.13Chapter 1.4 --- Related Work --- p.14Chapter 1.4.1 --- Using Vision Alone --- p.15Chapter 1.4.2 --- Integration of Vision and Touch --- p.15Chapter 1.4.3 --- Using Touch Sensing Alone --- p.17Chapter 1.4.3.1 --- Ronald S. Fearing's Work --- p.18Chapter 1.4.3.2 --- Peter K. Allen's Work --- p.22Chapter 1.5 --- Outline --- p.26Chapter 2 --- Geometric Models --- p.27Chapter 2.1 --- Introduction --- p.27Chapter 2.2 --- Superquadrics --- p.27Chapter 2.2.1 --- 2D Superquadrics --- p.27Chapter 2.2.2 --- 3D Superquadrics --- p.29Chapter 2.3 --- Model Recovery of Superquadric Models --- p.31Chapter 2.3.1 --- Problem Formulation --- p.31Chapter 2.3.2 --- Least Squares Optimization --- p.33Chapter 2.4 --- Free-Form Deformations --- p.34Chapter 2.4.1 --- Bernstein Basis --- p.36Chapter 2.4.2 --- B-Spline Basis --- p.38Chapter 2.5 --- Other Geometric Models --- p.41Chapter 2.5.1 --- Generalized Cylinders --- p.41Chapter 2.5.2 --- Hyperquadrics --- p.42Chapter 2.5.3 --- Polyhedral Models --- p.44Chapter 2.5.4 --- Function Representation --- p.45Chapter 3 --- Sensing Strategy --- p.54Chapter 3.1 --- Introduction --- p.54Chapter 3.2 --- Sensing Algorithm --- p.55Chapter 3.2.1 --- Assumption of objects --- p.55Chapter 3.2.2 --- Haptic Exploration Procedures --- p.56Chapter 3.3 --- Contour Tracing --- p.58Chapter 3.4 --- Tactile Sensor Data Preprocessing --- p.59Chapter 3.4.1 --- Data Transformation and Sensor Calibration --- p.60Chapter 3.4.2 --- Noise Filtering --- p.61Chapter 3.5 --- Curvature Determination --- p.64Chapter 3.6 --- Step Size Determination --- p.73Chapter 4 --- 3D Shape Reconstruction --- p.80Chapter 4.1 --- Introduction --- p.80Chapter 4.2 --- Correspondence Problem --- p.81Chapter 4.2.1 --- Affine Invariance Property of B-splines --- p.84Chapter 4.2.2 --- Point Inversion Problem --- p.87Chapter 4.3 --- Parameter Triple Interpolation --- p.91Chapter 4.4 --- 3D Object Shape Reconstruction --- p.94Chapter 4.4.1 --- Heuristic Approach --- p.94Chapter 4.4.2 --- Closed Contour Recovery --- p.97Chapter 4.4.3 --- Control Lattice Recovery --- p.102Chapter 5 --- Implementation --- p.105Chapter 5.1 --- Introduction --- p.105Chapter 5.2 --- Implementation Tool - MATLAB --- p.105Chapter 5.2.1 --- Optimization Toolbox --- p.107Chapter 5.2.2 --- Splines Toolbox --- p.108Chapter 5.3 --- Geometric Model Implementation --- p.109Chapter 5.3.1 --- FFD Examples --- p.111Chapter 5.4 --- Shape Reconstruction Implementation --- p.112Chapter 5.5 --- 3D Model Reconstruction Examples --- p.120Chapter 5.5.1 --- Example 1 --- p.120Chapter 5.5.2 --- Example 2 --- p.121Chapter 6 --- Conclusion --- p.128Chapter 6.1 --- Future Work --- p.129Appendix --- p.133Bibliography --- p.14

Haptics-based Modeling and Simulation of Micro-Implants Surgery

Ph.DDOCTOR OF PHILOSOPH

3-D surface modelling of the human body and 3-D surface anthropometry

This thesis investigates three-dimensional (3-D) surface modelling of the human body and 3-D surface anthropometry. These are two separate, but closely related, areas. 3-D surface modelling is an essential technology for representing and describing the surface shape of an object on a computer. 3-D surface modelling of the human body has wide applications in engineering design, work space simulation, the clothing industry, medicine, biomechanics and animation. These applications require increasingly realistic surface models of the human body. 3-D surface anthropometry is a new interdisciplinary subject. It is defined in this thesis as the art, science, and technology of acquiring, modelling and interrogating 3-D surface data of the human body. [Continues.

Collision Detection and Merging of Deformable B-Spline Surfaces in Virtual Reality Environment

This thesis presents a computational framework for representing, manipulating and merging rigid and deformable freeform objects in virtual reality (VR) environment. The core algorithms for collision detection, merging, and physics-based modeling used within this framework assume that all 3D deformable objects are B-spline surfaces. The interactive design tool can be represented as a B-spline surface, an implicit surface or a point, to allow the user a variety of rigid or deformable tools. The collision detection system utilizes the fact that the blending matrices used to discretize the B-spline surface are independent of the position of the control points and, therefore, can be pre-calculated. Complex B-spline surfaces can be generated by merging various B-spline surface patches using the B-spline surface patches merging algorithm presented in this thesis. Finally, the physics-based modeling system uses the mass-spring representation to determine the deformation and the reaction force values provided to the user. This helps to simulate realistic material behaviour of the model and assist the user in validating the design before performing extensive product detailing or finite element analysis using commercially available CAD software. The novelty of the proposed method stems from the pre-calculated blending matrices used to generate the points for graphical rendering, collision detection, merging of B-spline patches, and nodes for the mass spring system. This approach reduces computational time by avoiding the need to solve complex equations for blending functions of B-splines and perform the inversion of large matrices. This alternative approach to the mechanical concept design will also help to do away with the need to build prototypes for conceptualization and preliminary validation of the idea thereby reducing the time and cost of concept design phase and the wastage of resources

Rapid prototyping using a precision robotic manipulator

A rapid prototyping system using a precision robotic manipulator has been developed. The system is comprised of a latest personal computer (Pentium II, 300 MHz, 128 MB RAM and 5 GB hard disk capacity), interfacing system (PS-23 indexer, KS-drives and servomotors), a four degrees of freedom precision manipulator and a ball nosed end milling equipment. The hardware is integrated with the AutoSurf (CAD software), which is used in designing engineering models, section cut the surface models and changing graphic file into DXF files (neutral format files). The AutoLISP (AutoSurf programming language) has been used to simulate the additive prototyping process. The hardware is also linked with the self-developed CAM programs for data processing and motion control. With the above hardware and software configuration, subtractive prototyping models have been produced successfully. Simple additive prototyping process was also simulated graphically in AutoSurf environment. The CAM programs were also tested to be fine with the additive prototyping models’ data files. Generally, the rapid prototyping system using the precision robotic manipulator has the advantage of being cheaper, effective, time and space saving, with dual purposes (subtractive and additive processes) and it is an all in one system

Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas

The main interest of this thesis consists of the study and implementation of postprocessors to adapt the toolpath generated by a Computer Aided Manufacturing (CAM) system to a complex robotic workcell of eight joints, devoted to the rapid prototyping of 3D CAD-defined products. It consists of a 6R industrial manipulator mounted on a linear track and synchronized with a rotary table. To accomplish this main objective, previous work is required. Each task carried out entails a methodology, objective and partial results that complement each other, namely: - It is described the architecture of the workcell in depth, at both displacement and joint-rate levels, for both direct and inverse resolutions. The conditioning of the Jacobian matrix is described as kinetostatic performance index to evaluate the vicinity to singular postures. These ones are analysed from a geometric point of view. - Prior to any machining, the additional external joints require a calibration done in situ, usually in an industrial environment. A novel Non-contact Planar Constraint Calibration method is developed to estimate the external joints configuration parameters by means of a laser displacement sensor. - A first control is originally done by means of a fuzzy inference engine at the displacement level, which is integrated within the postprocessor of the CAM software. - Several Redundancy Resolution Schemes (RRS) at the joint-rate level are compared for the configuration of the postprocessor, dealing not only with the additional joints (intrinsic redundancy) but also with the redundancy due to the symmetry on the milling tool (functional redundancy). - The use of these schemes is optimized by adjusting two performance criterion vectors related to both singularity avoidance and maintenance of a preferred reference posture, as secondary tasks to be done during the path tracking. Two innovative fuzzy inference engines actively adjust the weight of each joint in these tasks.Andrés De La Esperanza, FJ. (2011). Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10627Palanci