The Space within Fisherman's Folly: Playing with a Puzzle in Mereotopology

Abstract

In this paper we propose a spatial ontology for reasoning about holes, rigid objects and a string, taking a classical puzzle as a motivating example. In this ontology the domain is composed of spatial regions whereby a theory about holes is defined over a mereotopological basis. Within this theory we define a data structure, named chain, that facilitates a clear and efficient representation of the puzzle states and its solution.     

Localization,Exploration, and Navigation Based on Qualitative Angle Information

Abstract

Three of the major problems in building autonomous mobile robots are localization, exploration, and navigation. This paper investigates how well different qualitative methods based on angle information, most of them originally invented for representation of spatial knowledge, are suited for addressing these problems. It combines results from discrete and computational geometry with methods from qualitative spatial reasoning, gaining some new insights on the complexity of robot navigation. It turns out that essentially only with panoramas (special roundviews) the qualitative localization problem can be solved in a satisfactory manner. The exploration problem (qualitative map building), remains difficult for all considered approaches.     

Path visualization: a method for objective measurement of spatial visualization

ABSTRACT

The ability to mentally represent spatial information is a fundamental cognitive process. To many people, this process feels a bit like visual perception, hence the term ‘spatial visualization’. In this paper, we describe a method for measuring the accuracy of spatial visualization, specifically visualization of a complex path in imaginary space. A critical feature of this method (called Path Visualization) is that it relies on the detection of intersections in a visualized path. Intersection detection is an inherently spatial task that requires a spatial representation. In this paper, we show how the Path Visualization method works, and how it can be customized to address several key research issues in human spatial cognition.     

Qualitative Spatial Reasoning for Topological Map Learning

Abstract

In this paper we investigate the application of qualitative spatial reasoning methods for learning the topological map of an unknown environment. We develop a topological mapping framework that achieves robustness against ambiguity in the available information by tracking all possible graph hypotheses simultaneously. We then exploit spatial reasoning to reduce the space of possible hypotheses. The considered constraints are qualitative direction information and the assumption that the map is planar. We investigate the effects of absolute and relative direction information using two different spatial calculi and combine the approach with a real mapping system based on Voronoi graphs.     

Exploring Regional Variation in Spatial Language Using Spatially Stratified Web-Sampled Route Direction Documents

Spatial language, such as route directions, can be analyzed to shed light on how humans communicate and conceptualize spatial knowledge. This article details a computational linguistic approach using route directions to study regional variations in spatial language. We developed a web-sourcing approach to collect human-generated route direction documents on a geographical scale. Specifically, we built the Spatially strAtified Route Direction (SARD) Corpus through automated scraping, classifying, and georeferencing of route directions. Based on semantic categories of cardinal and relative direction terms, the analysis of the SARD Corpus reveals significant differences and patterns on both national (United States, United Kingdom, and Australia) and regional (contiguous U.S. states) levels. Combining computational linguistics and georeferencing approaches offers the potential for extending classic spatial linguistic studies.     

Spatial Vagueness and Second-Order

This paper presents a geometric characterization of geographic objects with vague boundaries. Since the framework is based on ordering geometry and does not rely on numerical concepts, it can be applied to qualitative spatial reasoning. The characterization describes vague regions and gradual transitions between two vague regions. This approach takes into account that the region of all points that definitely belong to an object is also vague, called higher-order vagueness. Higher-order vagueness is usually neglected by theories modeling spatial vagueness. The approach distinguishes firstand second-order vague regions and characterizes the gradual transitions of second-order vague regions. These gradual transitions allow transitions within transitions. In general, it is not possible to reduce higher-order vagueness to first-order vagueness. Using a spatial ordering structure the article shows when second-order vagueness is useful and examines the relationship between first- and second-order vagueness. An example shows how second-order vagueness can be used to represent geographic objects.     

Mining Spatial Associations with Limited Sensory Information

Abstract

Human navigation in an unknown environment requires an understanding of the spatial relationships of the terrain. For example, a soldier who is on a reconnaissance mission in a new city needs to “know” the spatial layout of the surroundings with high confidence. Oftentimes, this understanding must be acquired within a very short amount of time and with limited sensory inputs. The soldier would benefit from a digital avatar that draws inferences about the spatial layout of the city based on an initial set of observations and guides the soldier either in further exploring the environment or in making decisions based on these inferences. In this paper, we present and evaluate an inductive approach to learning spatial associations using sensory data that is available from the simulation environment of a computer game, Unreal Tournament. We study two kinds of spatial relationships between nodes on a level of a game map: nodes that are placed near each other to satisfy some spatial requirement and nodes that are placed near each other to satisfy the design preferences of a level architect. We show that we can infer both kinds of relationships using an association rule mining algorithm. Furthermore, we show how to use an ontology to distinguish between these relationships in order to discover different types of spatial arrangements on a specific map. We discuss how the inferred associations can be used to control an avatar that makes recommendations for navigating unexplored areas on a map. We conclude with some thoughts on the applicability of our methods to scenarios in the real world, beyond the simulation environment of a game, and on how the learned associations can be represented and queried by a simple question-answer type system.     

Analyzing Qualitative Spatio-Temporal Calculi using Algebraic Geometry

Abstract

Qualitative spatial reasoning is based on calculi which comprise relations and operation tables that encode operations like relation composition. Designing a calculus involves determining these tables and analyzing reasoning properties—a demanding task that is susceptible to errors if performed manually. This paper is concerned with automating computation of operation tables and analysis of qualitative calculi over real-valued domains like the plane ². We present an approach to specify qualitative relations using polynomial equations that allows methods from algebraic geometry to be applied. This paper shows how reasoning with qualitative relations can be posed algebraically and demonstrates algebraic reasoning using Gröbner base analysis. We evaluate this approach and describe our implementation, which is freely available as part of the spatial reasoning toolbox SparQ.     

基于ESO的用户星天线跟踪指向控制技术

基于独特的非线性扩张状态观测器(ESO),提出了一种用户卫星天线跟踪指向控制系统。该系统由程序跟踪内环和自动跟踪外环组成。内环控制器由三阶ESO、线性比例微分控制律和静态解耦律组成。外环控制器为一简单的积分控制器。ESO能够在不依赖天线模型的情况下估计出系统状态和总扰动(称为扩张状态)。利用该扩张状态实现动态反馈补偿,则天线系统被简化为解耦的积分系统。基于ESO设计天线控制系统,无需精确的用户卫星天线模型。仿真结果表明,提出的天线控制系统具有较高的跟踪指向性能和对干扰和不确定性具有较强的鲁棒性。     

张拉整体伸展臂的构建方法研究

臂状张拉整体结构转化为张拉整体伸展臂的方案被分析研究。首先，构建臂状张拉整体结构的数学模型。而后，基于臂状张拉整体结构，通过受力变形分析，获得了此结构在轴向外载作用下，其整体高度、截面直径和构件长度变化规律。依据分析结果，研究驱动此结构折叠的方案和索构件弹性化方案。利用仿真分析和模型实验，对所获得的机构方案的可行性和合理性进行了分析验证。通过研究得到：将多层张拉整体斜索和鞍索柔性化，驱动附加索更容易实现折展；张拉整体层数增多时，驱动附加索可减小控制难度；多层张拉整体占用空间主要受高度影响。通过分析，获得了一种可行的张拉整体伸展臂设计方案。研究中应用的由折叠方式推导展开方案的分析思路也能够为张拉整体结构的机构化研究提供借鉴。     

基于图像识别技术的火箭飞行时序判读

在运载火箭开展射前综合测试时,控制系统在预先指定的飞行时序向末端发送一系列指令,指示末端设备做出相应动作,以达成对应的目标。这些动作主要依赖火工品完成,这些动作变化会体现在火工品等效器指示灯上。当前控制系统无法检测到末端等效器的电流情况变化,因此无法对末端动作进行有效监测,测试缺乏可靠性、准确性与可追溯性的问题亟需改善。通过综合运用人工智能、数字图像处理与计算机视觉技术,经由特征匹配、指示灯定位、指示灯状态建模等步骤,可对末端火工品等效器状态变化实现精准监测,进而实现飞行时序自动判读。与标准判据比对后,本文提出的火箭飞行时序判读系统准确率可达98.89%。     

On Embedding a Qualitative Representation in a Two-Dimensional Plane

Abstract

This paper discusses embedding in a two-dimensional plane a symbolic representation for spatial data using the simple objects, points (P), lines (L), circuits (C), and areas (A). We have proposed PLCA as a new framework for a qualitative spatial reasoning. In a PLCA expression, the entire figure is represented in a form in which all the objects are related. We investigate the conditions for two-dimensional realizability of a PLCA expression, and derive the relation that the numbers of objects in a PLCA expression should have. In this process, we use the well-known Euler's formula. We also give an algorithm for drawing the figure of the PLCA expression that satisfies this condition in a two-dimensional plane and prove its correctness. The algorithm generates a quantitative expression from qualitative expression.     

基于功能单元的分层诊断技术研究及在航天器中的应用

复杂系统多故障诊断的计算复杂性一直是一个难题。现给出了一种定性诊断模型:将功能单元引入到系统建模中并与结构抽象技术相结合构建分层诊断模型(SPS树)。推理时运用分层诊断策略及相关诊断定理,减少了多故障诊断的计算量,提高了效率。此方法在某卫星电源系统中得到了应用。证明该方法诊断速度快,诊断结果完备,可以实现对未知故障的诊断,适用于卫星这类复杂系统的多故障诊断。     

The acquisition of survey knowledge for local and global landmark configurations under time pressure

The influence of stress states on cognition is widely recognized. However, the manner in which stress affects survey knowledge acquisition is still unresolved. For the present study, we investigated whether survey knowledge acquisition during a stressful task (i.e., under time pressure) is more accurate for the mental representation of global or local landmarks. Participants navigated through virtual cities with a navigation aid and explicit learning instructions for different landmark configurations. Participants’ judgments of relative direction (JRDs) suggest that global landmark configurations were not represented more accurately than local landmark configurations and that survey knowledge acquisition was not impaired under time pressure. In contrast to prior findings, our results indicate the limitations of the utility of global landmarks for spatial knowledge acquisition.     

基于神经网络的潜在通路分析

针对传统潜在通路分析过程复杂、劳动量大的缺陷，提出了基于神经网络的潜在通路分析。神经网络的输入为系统元件的定性状态组合，输出为预测实现功能组合。利用元件与设计功能之间的关系，形成神经网络训练样本。经过训练后，神经网络预测所有元件状态组合实现的功能，然后通过与设计功能的比较，确定电路的潜在通路。经仿真验证，此方法进行潜在通路分析时的正确率达到了92％，而且分析的工作量比较小。     

Wayfinding Through Orientation

Dominant approaches in computer-assisted wayfinding support adhere to the deeply problematic principles of turn-by-turn navigation. In this article, we suggest a new approach called “Wayfinding Through Orientation,” which supports the acquisition of spatial knowledge and cognitive mapping for advancing the user’s spatial orientation. Being oriented on one’s way is a prerequisite to enabling people to verify instructions and to incorporate new spatial information into their existing knowledge structure. In three studies described in this article we first present empirical evidence that people can be supported in survey knowledge acquisition through suitable wayfinding instructions. Consequently, we explore orientation information in human wayfinding instructions. Finally, we outline how orientation information can be communicated within a prototypically implemented navigation assistance system.     

Transformations and representations supporting spatial perspective taking

Spatial perspective taking is the ability to reason about spatial relations relative to another’s viewpoint. Here, we propose a mechanistic hypothesis that relates mental representations of one’s viewpoint to the transformations used for spatial perspective taking. We test this hypothesis using a novel behavioral paradigm that assays patterns of response time and variation in those patterns across people. The results support the hypothesis that people maintain a schematic representation of the space around their body, update that representation to take another’s perspective, and thereby to reason about the space around their body. This is a powerful computational mechanism that can support imitation, coordination of behavior, and observational learning.