Geometric aspects of the casting process

Manufacturing is the process of converting raw materials into useful products. Among the most important manufacturing processes, casting is a commonly used manufacturing process for plastic and metal objects. The industrial casting process consists of two stages. First, liquid is filled into a cavity formed by two cast parts. After the liquid has hardened, one cast part retracts, carrying the object with it. Afterwards, the object is ejected from the retracted cast part. In both retraction and ejection steps, the cast parts and the object should not be damaged, so that the quality of final object is guaranteed and the cast parts can be reused to produce another object. This mode of production is called ``mass production''. Due to the geometric nature of the casting process, many geometric problems arise in the automation of casting. The problems we address here concern this aspect: Given a 3-dimensional object, is there a cast for it whose parts can be removed after the liquid has solidified? An object for which this is the case is called castable. We consider the castability problem in three different casting models with a two-part cast. In the first casting model, two parts must be removed in opposite directions. There are two cases depending on whether the removal direction is specified in advance or not. The second model is identical to the first casting model, except that the cast machinery has a certain level of uncertainty in its directional movement. In the third model, the two cast parts are to be removed in two given directions and these directions need not be opposite. For all three casting models, we give complete characterizations of castability, and obtain algorithms to verify these conditions for polyhedral parts. In manufacturing, features of an object imply manufacturing information, which facilitates the process of analyzing manufacturability and the automated design of a cast for the object. A small hole or a depression on the boundary of an object, for example, restricts the set of removal directions for which this object is castable, since the portion of the cast in the hole or in the depression must be removed from the object without breaking the object. We define a geometric feature, the cavity, which is related to the castability of objects, and provide algorithms to extract it from objects

Planning dextrous robot hand grasps from range data, using preshapes and digit trajectories

Dextrous robot hands have many degrees of freedom. This enables the manipulation of objects between the digits of the dextrous hand but makes grasp planning substantially more complex than for parallel jaw grippers. Much of the work that addresses grasp planning for dextrous hands concentrates on the selection of contact sites to optimise stability criteria and ignores the kinematics of the hand. In more complete systems, the paradigm of preshaping has emerged as dominant. However, the criteria for the formation and placement of the preshapes have not been adequately examined, and the usefulness of the systems is therefore limited to grasping simple objects for which preshapes can be formed using coarse heuristics.In this thesis a grasp metric based on stability and kinematic feasibility is introduced. The preshaping paradigm is extended to include consideration of the trajectories that the digits take during closure from preshape to final grasp. The resulting grasp family is dependent upon task requirements and is designed for a set of "ideal" object-hand configurations. The grasp family couples the degrees of freedom of the dextrous hand in an anthropomorphic manner; the resulting reduction in freedom makes the grasp planning less complex. Grasp families are fitted to real objects by optimisation of the grasp metric; this corresponds to fitting the real object-hand configuration as close to the ideal as possible. First, the preshape aperture, which defines the positions of the fingertips in the preshape, is found by optimisation of an approximation to the grasp metric (which makes simplifying assumptions about the digit trajectories and hand kinematics). Second, the full preshape kinematics and digit closure trajectories are calculated to optimise the full grasp metric.Grasps are planned on object models built from laser striper range data from two viewpoints. A surface description of the object is used to prune the space of possible contact sites and to allow the accurate estimation of normals, which is required by the grasp metric to estimate the amount of friction required. A voxel description, built by ray-casting, is used to check for collisions between the object and the robot hand using an approximation to the Euclidean distance transform.Results are shown in simulation for a 3-digit hand model, designed to be like a simplified human hand in terms of its size and functionality. There are clear extensions of the method to any dextrous hand with a single thumb opposing multiple fingers and several different hand models that could be used are described. Grasps are planned on a wide variety of curved and polyhedral object

構造化データに対する予測手法：グラフ，順序，時系列

京都大学新制・課程博士博士(情報学)甲第23439号情博第769号新制||情||131(附属図書館)京都大学大学院情報学研究科知能情報学専攻(主査)教授 鹿島 久嗣, 教授 山本 章博, 教授 阿久津 達也学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

Lunar navigation study, sections 1 through 7 Final report, Jun. 1964 - May 1965

Lunar navigation analysis using passive nongyro, inertial navigation, and radio frequency technolog

Algorithms for generating multi-stage molding plans for articulated assemblies

Plastic products such as toys with articulated arms, legs, and heads are traditionally produced by first molding individual components separately, and then assembling them together. A recent alternative, referred to as in-mold assembly process, performs molding and assembly steps concurrently inside the mold itself. The most common technique of performing in-mold assembly is through multi-stage molding, in which the various components of an assembly are injected in a sequence of molding stages to produce the final assembly. Multi-stage molding produces better-quality articulated products at a lower cost. It however, gives rise to new mold design challenges that are absent from traditional molding. We need to develop a molding plan that determines the mold design parameters and sequence of molding stages. There are currently no software tools available to generate molding plans. It is difficult to perform the planning manually because it involves evaluating large number of combinations and solving complex geometric reasoning problems. This dissertation investigates the problem of generating multi-stage molding plans for articulated assemblies. The multi-stage molding process is studied and the underlying governing principles and constraints are identified. A hybrid planning framework that combines elements from generative and variant techniques is developed. A molding plan representation is developed to build a library of feasible molding plans for basic joints. These molding plans for individual joints are reused to generate plans for new assemblies. As part of this overall planning framework, we need to solve the following geometric subproblems -- finding assembly configuration that is both feasible and optimal, finding mold-piece regions, and constructing an optimal shutoff surface. Algorithms to solve these subproblems are developed and characterized. This dissertation makes the following contributions. The representation for molding plans provides a common platform for sharing feasible and efficient molding plans for joints. It investigates the multi-stage mold design problem from the planning perspective. The new hybrid planning framework and geometric reasoning algorithms will increase the level of automation and reduce chances of design mistakes. This will in turn reduce the cost and lead-time associated with the deployment of multi-stage molding process

Application of general semi-infinite Programming to Lapidary Cutting Problems

We consider a volume maximization problem arising in gemstone cutting industry. The problem is formulated as a general semi-infinite program (GSIP) and solved using an interiorpoint method developed by Stein. It is shown, that the convexity assumption needed for the convergence of the algorithm can be satisfied by appropriate modelling. Clustering techniques are used to reduce the number of container constraints, which is necessary to make the subproblems practically tractable. An iterative process consisting of GSIP optimization and adaptive refinement steps is then employed to obtain an optimal solution which is also feasible for the original problem. Some numerical results based on realworld data are also presented

On the Pricing of Forward Starting Options under Stochastic Volatility

We consider the problem of pricing European forward starting options in the presence of stochastic ­volatility. By performing a change of measure using the asset price at the time of strike determination as a numeraire, we derive a closed-form solution based on Heston’s model of stochastic volatility