A Connectivity-Based Method for Enhancing Sampling in Probabilistic Roadmap Planners

The motion planning is a difficult problem but nevertheless, a crucial part of robotics. The probabilistic roadmap planners have shown to be an efficient way to solve these planning problems. In this paper, we present a new algorithm that is based on the principles of the probabilistic roadmap planners. Our algorithm enhances the sampling by intelligently detecting which areas of the configuration space are easy and which parts are not. The algorithm then biases the sampling only to the difficult areas that may contain narrow passages. Our algorithm works by dividing the configuration space into regions at the beginning and then sampling configurations inside each region. Based on the connectivity of the roadmap inside each region, our algorithm aims to detect whether the region is easy or difficult. We tested our algorithm with three different simulated environments and compared it with two other planners. Our experiments showed that with our method it is possible to achieve significantly better results than with other tested planners. Our algorithm was also able to reduce the size of roadmaps.     

Probabilistic databases for decision analysis

A probabilistic database is defined in a previous article [R. Cavallo and M. Pittarelli, Proc. 13th Int. Conf. on Very Large Databases (VLDB); 1987; see Ref. 9] as a collection of probability distributions over Cartesian products of finite variable domains. the concept is extended here to accommodate interval-valued probabilities. Algebraic operations for both real- and interval-valued probabilities databases analogous to those for relational databases are defined. Techniques for making inferences regarding joint distributions on subsets of the variables over which a probabilistic database is defined are developed. These are illustrated through application to a problem of decision analysis under partial uncertainty. Connections between the probabilistic database formalism and other forms of data representation are discussed.     

Probabilistic posture classification for Human-behavior analysis

Computer vision and ubiquitous multimedia access nowadays make feasible the development of a mostly automated system for human-behavior analysis. In this context, our proposal is to analyze human behaviors by classifying the posture of the monitored person and, consequently, detecting corresponding events and alarm situations, like a fall. To this aim, our approach can be divided in two phases: for each frame, the projection histograms (Haritaoglu et al., 1998) of each person are computed and compared with the probabilistic projection maps stored for each posture during the training phase; then, the obtained posture is further validated exploiting the information extracted by a tracking module in order to take into account the reliability of the classification of the first phase. Moreover, the tracking algorithm is used to handle occlusions, making the system particularly robust even in indoors environments. Extensive experimental results demonstrate a promising average accuracy of more than 95% in correctly classifying human postures, even in the case of challenging conditions.     

Probabilistic performance analysis for parallel search techniques

This paper discusses the performance analysis of two generic fundamental parallel search techniques on shared memory multi-processor systems in solving the constraint satisfaction problem (CSP). Probabilistic analysis on their expected computation steps needed and their inherent load-balancing capability is performed. Corresponding experimental results are alsoprovided to verify the correctness of the proposed analysis. This fundamental analysis approach can be further applied to various advanced parallel search techniques or various problem solving techniques on parallel platforms. This research was supported in part by the University of Texas at San Antonio under the Faculty Research Award program     

Performance analysis of path planners for car-like vehicles toward automatic parking control

A car parking control problem is difficult because of its non-holonomic constraints and complicated environmental geometry. We proposed Korea University Path Planner (KPP) in our prior work. KPP is an appropriate scheme for a car-like mobile robot in a parking environment. The purpose of this paper is to investigate the advantages of KPP through both quantitative and qualitative analyses. For comparison, numerical simulations have been carried out by the application of KPP and the conventional Rapidly exploring random tree method. This paper shows that KPP exhibits outstanding performance from the viewpoints of travel time and computational time.     

Probabilistic analysis of regularization

In order to use interpolated data wisely, it is important to have reliability and confidence measures associated with it. A method for computing the reliability at each point of any linear functional of a surface reconstructed using regularization is presented. The proposed method is to define a probability structure on the class of possible objects and compute the variance of the corresponding random variable. This variance is a natural measure for uncertainty, and experiments have shown it to correlate well with reality. The probability distribution used is based on the Boltzmann distribution. The theoretical part of the work utilizes tools from classical analysis, functional analysis, and measure theory on function spaces. The theory was tested and applied to real depth images. It was also applied to formalize a paradigm of optimal sampling, which was successfully tested on real depth images     

Probabilistic sensitivity analysis methods for general decision models

Probabilistic sensitivity analysis has previously been described for the special case of dichotomous decision trees. We now generalize these techniques for a wider range of decision problems. These methods of sensitivity analysis allow the analyst to evaluate the impact of the multivariate uncertainty in the data used in the decision model and to gain insight into the probabilistic contribution of each of the variables to the decision outcome. The techniques are illustrated using Monte Carlo simulation on a trichotomous decision tree. Application of these powerful tools permits the decision analyst to investigate the structure and limitations of more complex decision problems with inherent uncertainties in the data upon which the decisions are based. Probabilistic sensitivity measures can provide guidance into the allocation of resources to resolve uncertainty about critical components of medical decisions.     

New computer graphic tools for transportation planners

Three interactive graphic computer programs are described which aid transportation planners in data analysis and display: (1) FLOWMAP, which enables the interactive design of flow maps at a computer graphics terminal using origin-destination data; (2) FLOGRAF, which graphically displays traffic flows along a network using color computer graphics, and (3) TRANES, a transit system analysis program that displays the number and type of potential transit users within specified access limits of transit facilities. Typical applications in transportation planning are suggested for each of the programs and recommendations are made for future enhancements. Readily available sources of data are suggested which can be tapped to provide input to the programs.     

Probabilistic analysis of floating-point addition

Cybernetics and Systems Analysis -     

Probabilistic sequential independent components analysis

Under-complete models, which derive lower dimensional representations of input data, are valuable in domains in which the number of input dimensions is very large, such as data consisting of a temporal sequence of images. This paper presents the under-complete product of experts (UPoE), where each expert models a one-dimensional projection of the data. Maximum-likelihood learning rules for this model constitute a tractable and exact algorithm for learning under-complete independent components. The learning rules for this model coincide with approximate learning rules proposed earlier for under-complete independent component analysis (UICA) models. This paper also derives an efficient sequential learning algorithm from this model and discusses its relationship to sequential independent component analysis (ICA), projection pursuit density estimation, and feature induction algorithms for additive random field models. This paper demonstrates the efficacy of these novel algorithms on high-dimensional continuous datasets.     

Probabilistic dynamic analysis with ADINA

In structural analysis the extreme values of the structural response quantities are of primary interest. In the case of linear structures under stationary Gaussian random exicitations a probabilistic analysis provides the expected extreme values as well as confidence intervals in a mathematically rigorous way. The analysis becomes particularly simple in modal coordinates, if the damping matrix decouples. All quantities required for the probabilistic analysis are then readily obtained from the modal covariance matrices. The evaluation of these matrices by analytical integration is discussed. This method is computationally very effective and maintains full accuracy in the dynamic properties of the structural model. The implementation of the probabilistic analysis in ADINA is outlined. As an illustration, the seismic analysis of a structure under multiple support random excitation is presented.     

A GIS-based environmental modelling system for transportation planners

This paper describes a GIS-based environmental modelling system, termed TRAEMS, for use by transport planners in assessing the environmental effects of road traffic plans. The system utilises capabilities of GIS to integrate the output from a transport planning activity with land use information to model the environmental impacts of different road traffic scenarios. TRAEMS enables planners to test transport related environmental impacts at the same time as they are testing the traffic carrying efficiencies of network plans. The suitability of this type of environmental modelling for planning purposes is illustrated using a case study.     

Probabilistic analysis of a grouping algorithm

We study thegrouping by swapping problem, which occurs in memory compaction and in computing the exponential of a matrix. In this problem we are given a sequence ofn numbers drawn from {0,1, 2,...,m–1} with repetitions allowed; we are to rearrange them, using as few swaps of adjacent elements as possible, into an order such that all the like numbers are grouped together. It is known that this problem is NP-hard. We present a probabilistic analysis of a grouping algorithm calledMEDIAN that works by sorting the numbers in the sequence according to their median positions. Our results show that the expected behavior ofMEDIAN is within 10% of optimal and is asymptotically optimal asn/m or asn/m0.The work of this author was supported in part by the Texas Advanced Research Program under Grant 4096.     

Probabilistic analysis of a grouping algorithm

We study thegrouping by swapping problem, which occurs in memory compaction and in computing the exponential of a matrix. In this problem we are given a sequence ofn numbers drawn from {0,1, 2,...,m?1} with repetitions allowed; we are to rearrange them, using as few swaps of adjacent elements as possible, into an order such that all the like numbers are grouped together. It is known that this problem is NP-hard. We present a probabilistic analysis of a grouping algorithm calledMEDIAN that works by sorting the numbers in the sequence according to their median positions. Our results show that the expected behavior ofMEDIAN is within 10% of optimal and is asymptotically optimal asn/m→∞ or asn/m→0.     

可燃气云爆炸事故后果的概率分析

对事故后果进行分析．是安全评价的重要内容。可燃气体泄漏后发生蒸气云爆炸是一种重要的事故类型,由于人们对事故后果认识的局限、环境的影响、以及事故发展过程的复杂性,VCE后果分析中许多参数未能准确定义,部份输入参数取值具有随机性,不同取值使最终的分析结果相差很大。本文提出了一种事故后果的概率分析方法。通过事故的后果(死亡半径)及其发生的概率来反映后果严重程度,并基于蒙特卡罗模拟方法来计算事故后果的发生概率。本文对给定发生概率时如何确定死亡半径也进行了分析,采用基于支持向量机(SVM)的非线性回归估计方法对死亡半径进行估计。分析了VCE后果分析模型中的随机性参数及其取值,结合具体的应用实例,说明了该方法在LPG储罐蒸气云爆炸后果分析中的应用。     

Homotopic Roadmap Generation for Robot Motion Planning

Two robot paths are said to be in the same homotopic group if one can be obtained from the other by multiple small deformations. Knowledge of robot homotopic groups gives information regarding the obstacle structure and enables timely computation of optimal path. Making a roadmap which misses out on a single homotopic group in such approaches may lead to sub-optimal decisions. E.g. one may prefer to go through a very narrow corridor if that reduces the path length significantly, but not if the resulting path has too many such narrow segments. Similarly knowledge of homotopic groups may enable distribution and scheduling of robots across homotopic groups for decentralized planning of multiple robots. For an unstructured robot environment, sampling based approaches give an insight into homotopic groups. The aim of the work is to make a homotopy conscious Probabilistic Roadmap such that the roadmap is capable of generating paths corresponding to as many homotopic groups as possible. Experimental results confirm that the proposed approach gives the best results as compared to the other sampling techniques subject to the test scenarios run.     

Reachability-based feedback control of crystal size distribution in batch crystallization processes

In the paper, we investigate the controllability of crystallization processes by reachability analysis. Crystallization processes are governed by hyperbolic partial differential equations. Given a desired crystal size distribution, we study its reachability by the temperature control from the initial condition without seeding. When the desired crystal size distribution is reachable, we construct an admissible control steering the state to the desired distribution. Our construction is developed based on the discretized model. To ensure that the desired distribution be reached facing model uncertainty, we propose an output feedback control law to correct errors resulted from disturbed parameters of the model.     

中国RFID技术应用明确路线图

2004年10月,科技部会同14个部委启动《中国射频识别(RFID)技术政策白皮书》编写工作,编写专家组经过12稿修改,于2005年12月形成征求意见稿,在向相关部委征求意见后,最终完成了《中国射频识别(RFID)技术政策白皮书》编制。2006年6月9日,科技部组织召开《中国射频识别(RFID)技术政策白皮书》新闻发布会,倍受瞩目的《中国射频识别(RFID)技术政策白皮书》正式以国家技术产业政策的形式对外公布。