An Improvement of McMillan's Unfolding Algorithm

McMillan has recently proposed a new technique to avoid the state explosion problem in the verification of systems modelled with finite-state Petri nets. The technique requires to construct a finite initial part of the unfolding of the net. McMillan's algorithm for this task may yield initial parts that are larger than necessary (exponentially larger in the worst case). We present a refinement of the algorithm which overcomes this problem.     

Statistical Learning for Humanoid Robots

The complexity of the kinematic and dynamic structure of humanoid robots make conventional analytical approaches to control increasingly unsuitable for such systems. Learning techniques offer a possible way to aid controller design if insufficient analytical knowledge is available, and learning approaches seem mandatory when humanoid systems are supposed to become completely autonomous. While recent research in neural networks and statistical learning has focused mostly on learning from finite data sets without stringent constraints on computational efficiency, learning for humanoid robots requires a different setting, characterized by the need for real-time learning performance from an essentially infinite stream of incrementally arriving data. This paper demonstrates how even high-dimensional learning problems of this kind can successfully be dealt with by techniques from nonparametric regression and locally weighted learning. As an example, we describe the application of one of the most advanced of such algorithms, Locally Weighted Projection Regression (LWPR), to the on-line learning of three problems in humanoid motor control: the learning of inverse dynamics models for model-based control, the learning of inverse kinematics of redundant manipulators, and the learning of oculomotor reflexes. All these examples demonstrate fast, i.e., within seconds or minutes, learning convergence with highly accurate final peformance. We conclude that real-time learning for complex motor system like humanoid robots is possible with appropriately tailored algorithms, such that increasingly autonomous robots with massive learning abilities should be achievable in the near future.     

Approximate Quantified Constraint Solving by Cylindrical Box Decomposition

This paper applies interval methods to a classical problem in computer algebra. Let a quantified constraint be a first-order formula over the real numbers. As shown by A. Tarski in the 1930's, such constraints, when restricted to the predicate symbols <, = and function symbols +, ×, are in general solvable. However, the problem becomes undecidable, when we add function symbols like sin. Furthermore, all exact algorithms known up to now are too slow for big examples, do not provide partial information before computing the total result, cannot satisfactorily deal with interval constants in the input, and often generate huge output. As a remedy we propose an approximation method based on interval arithmetic. It uses a generalization of the notion of cylindrical decomposition—as introduced by G. Collins. We describe an implementation of the method and demonstrate that, for quantified constraints without equalities, it can efficiently give approximate information on problems that are too hard for current exact methods.     

The plenoptic illumination function

Image-based modeling and rendering has been demonstrated as a cost-effective and efficient approach to virtual reality applications. The computational model that most image-based techniques are based on is the plenoptic function. Since the original formulation of the plenoptic function does not include illumination, most previous image-based virtual reality applications simply assume that the illumination is fixed. We propose a formulation of the plenoptic function, called the plenoptic illumination function, which explicitly specifies the illumination component. Techniques based on this new formulation can be extended to support relighting as well as view interpolation. To relight images with various illumination configurations, we also propose a local illumination model, which utilizes the rules of image superposition. We demonstrate how this new formulation can be applied to extend two existing image-based representations, panorama representation such as QuickTime VR and two-plane parameterization, to support relighting with trivial modifications. The core of this framework is compression, and we therefore show how to exploit two types of data correlation, the intra-pixel and the inter-pixel correlations, in order to achieve a manageable storage size.     

Output tracking control of MIMO fuzzy nonlinear systems using variable structure control approach

The output tracking control problem for nonlinear systems in the presence of both parameter perturbations and external disturbances is studied. Our approach is based on the Takagi-Sugeno (T-S) fuzzy modeling method and a variable structure control (VSC) technique. Therefore, the systems considered are not and need not be in the triangular and parametric strict-feedback form, which are prevalent among adaptive model following control for nonlinear systems, or in the normal form, which pervades almost all existing results in neuro-fuzzy model following control approach. We first study the problem of stabilization of T-S fuzzy systems by using a VSC technique. A method for the design of a switching surface based on linear matrix inequalities is developed and a stabilizing controller based on a reaching law concept in the presence of both parameter perturbations and external disturbances is proposed. Then, the method is extended to design controllers for output tracking of T-S fuzzy nonlinear systems in two cases, i.e. systems which possess the so-called strong passive subsystems and strong stable zero dynamics, respectively. Finally, illustrative examples are presented to demonstrate the whole design procedure from the original nonlinear systems to their fuzzification and finally to the realization of the desired controllers. Simulation results show that the goal of output tracking can be achieved by the proposed controllers.     

Role of base plate rotational speed in controlling spheroid size distribution and minimizing oversize particle formation during spheroid production by rotary processing

The occurrence of material adhesion and formation of oversize particles in the product yield during one-pot spheroid production by rotary processing leads to a less predictable process and a decrease in the usable portion of the total product yield obtained from each production run. The use of variable speeds of the rotating frictional base plate during the spheronization run was investigated for achieving optimal spheroid production. When the base plate speed was increased during liquid addition, the greater centrifugal forces generated improved liquid distribution and the mixing of the moist powder mass, resulting in a decrease in the amount of oversize particles formed. When the base plate was maintained at a high speed throughout the run, the amount of oversize particles and mean spheroid size increased, and a greater “between batch” mean spheroid size variability was also observed. The findings showed that, when higher speeds were used, the residence time must be adjusted accordingly to avoid excessive coalescence and growth while maintaining even liquid distribution. A “low-high-low” speed variation during rotary processing may be used to produce spheroids with a narrow size distribution and with a minimal amount of oversize particles in the total product yield.     

Metal–support interactions on rhodium model catalysts

Metal–support interactions on supported rhodium catalysts were studied by using specially prepared Rh/TiO₂/Mo model systems. For their characterization and the analysis of modifications due to various heat treatments several surface analytical methods were applied: low-energy ion scattering, X-ray photoemission spectroscopy and thermal desorption spectroscopy. Heating in ultrahigh vacuum to 670 K leads to Rh agglomeration followed (above 720 K) by encapsulation including the formation of reduced titanium oxide species. These morphological and chemisorption changes are reversible upon reoxidation and low-temperature reduction and thus exhibit the characteristic features of strong metal–support interactions. For the effective mechanism a reaction is suggested that involves oxygen chemisorption on the Rh clusters and partial reduction of the surrounding support oxide.     

A Gesture Based Interface for Human-Robot Interaction

Service robotics is currently a highly active research area in robotics, with enormous societal potential. Since service robots directly interact with people, finding natural and easy-to-use user interfaces is of fundamental importance. While past work has predominately focussed on issues such as navigation and manipulation, relatively few robotic systems are equipped with flexible user interfaces that permit controlling the robot by natural means. This paper describes a gesture interface for the control of a mobile robot equipped with a manipulator. The interface uses a camera to track a person and recognize gestures involving arm motion. A fast, adaptive tracking algorithm enables the robot to track and follow a person reliably through office environments with changing lighting conditions. Two alternative methods for gesture recognition are compared: a template based approach and a neural network approach. Both are combined with the Viterbi algorithm for the recognition of gestures defined through arm motion (in addition to static arm poses). Results are reported in the context of an interactive clean-up task, where a person guides the robot to specific locations that need to be cleaned and instructs the robot to pick up trash.     

控制系统的鲁棒性能设计与判据

本文对控制系统鲁棒性能设计中的Ｈ∝、μ和Ｑ判据进行了分析和对比，指出结构奇异值（μ）才是控制系统鲁棒性能的充要性判据。文中还配有例题进行说明。     

超微粉体的制备（一）

在搜集较多文献资料的基础上,撰写了“超微粉体的制备”一文,由于内容较多,现分成五篇连载,望对该领域感兴趣及从事这方面教学和科研的读者有所帮助。