Stabilization of underwater vehicle dynamics with symmetry-breaking potentials

We show how to stabilize, in stages, arbitrary steady translations of an underwater vehicle with feedback that derives from a potential and deliberately breaks symmetry in the dynamics. First, rotational symmetry is broken to ensure stability in the momentum parameters. Then, translational symmetry is broken to prevent drift. Stability of the closed-loop system is proved using the energy-Casimir method. A resulting property of the control law is robustness to model parameter uncertainty.     

Symmetry Definitions for Constraint Satisfaction Problems

We review the many different definitions of symmetry for constraint satisfaction problems (CSPs) that have appeared in the literature, and show that a symmetry can be defined in two fundamentally different ways: as an operation preserving the solutions of a CSP instance, or else as an operation preserving the constraints. We refer to these as solution symmetries and constraint symmetries. We define a constraint symmetry more precisely as an automorphism of a hypergraph associated with a CSP instance, the microstructure complement. We show that the solution symmetries of a CSP instance can also be obtained as the automorphisms of a related hypergraph, the k-ary nogood hypergraph and give examples to show that some instances have many more solution symmetries than constraint symmetries. Finally, we discuss the practical implications of these different notions of symmetry.     

Symmetry building Monte Carlo-based crystal structure prediction

Methods are presented that allow for the automatic increase and preservation of symmetry during global optimization of crystal structures. This systematic building of symmetry allows for its incorporation into structure prediction simulations even when the space group information is not known a priori. It is shown that simulations that build and maintain symmetry converge much more rapidly to ground state crystal structures than when symmetry is ignored, allowing for the treatment of unit cells much larger than would otherwise be possible, especially when beginning from the P1 space group.     

Symmetry Breaking Constraints for Value Symmetries in Constraint Satisfaction

Constraint satisfaction problems (CSPs) sometimes contain both variable symmetries and value symmetries, causing adverse effects on CSP solvers based on tree search. As a remedy, symmetry breaking constraints are commonly used. While variable symmetry breaking constraints can be expressed easily and propagated efficiently using lexicographic ordering, value symmetry breaking constraints are often difficult to formulate. In this paper, we propose two methods of using symmetry breaking constraints to tackle value symmetries. First, we show theoretically when value symmetries in one CSP correspond to variable symmetries in another CSP of the same problem. We also show when variable symmetry breaking constraints in the two CSPs, combined using channeling constraints, are consistent. Such results allow us to tackle value symmetries efficiently using additional CSP variables and channeling constraints. Second, we introduce value precedence, a notion which can be used to break a common class of value symmetries, namely symmetries of indistinguishable values. While value precedence can be expressed using inefficient if-then constraints in existing CSP solvers, we propose efficient propagation algorithms for implementing global value precedence constraints. We also characterize several theoretical properties of the value precedence constraints. Extensive experiments are conducted to verify the feasibility and efficiency of the two proposals.     

Evolutionary learning of a fuzzy controller for wall-following behavior in mobile robotics

The design of fuzzy controllers for the implementation of behaviors in mobile robotics is a complex and highly time-consuming task. The use of machine learning techniques such as evolutionary algorithms or artificial neural networks for the learning of these controllers allows to automate the design process. In this paper, the automated design of a fuzzy controller using genetic algorithms for the implementation of the wall-following behavior in a mobile robot is described. The algorithm is based on the iterative rule learning approach, and is characterized by three main points. First, learning has no restrictions neither in the number of membership functions, nor in their values. In the second place, the training set is composed of a set of examples uniformly distributed along the universe of discourse of the variables. This warrantees that the quality of the learned behavior does not depend on the environment, and also that the robot will be capable to face different situations. Finally, the trade off between the number of rules and the quality/accuracy of the controller can be adjusted selecting the value of a parameter. Once the knowledge base has been learned, a process for its reduction and tuning is applied, increasing the cooperation between rules and reducing its number.     

科技美学中对称、对偶在日常教学中的应用

对称、对偶都是美学中的基本要素.作为一名教育工作者在教学活动中适当运用美学元素作为教学手段,不断改进教学方法,而且能够从中收益,获得美的享受,是一件十分快乐的事情.本文从应用的角度阐述美学原理在具体教学实践中的巧用,结合多年的教学体会,在电工基础、物理学、信号与系统等课程领域,运用对称、对偶等美学元素,使教学活动更加生动、形象.既活跃了课堂气氛,又加深了学生的理解和记忆,取得了良好的教学效果.     

LOGUE: an architecture for task and behavior object transmission among multiple autonomous robots

This paper proposes a new communication and control architecture which improves the capability and the flexibility of multiple autonomous robot systems in performing a complicated task and coping with unpredictable situations. This system treats robot’s information as a Behavior Element Object (BEO) and a Task Object (TO) in terms of Object Oriented paradigm. Both BEO and TO can be serialized, so they can be communicated among the robots and behavior server system in the network. The action manager module, device module, and some checking mechanisms are also designed for executing new TO or BEO sent from other robots or a server system. A simulation and basic experiments are presented for a situation of robots’ relief for an emergency purpose.     

Symmetry reductions for model checking of concurrent dynamic software

Symmetry reduction techniques exploit symmetries that occur during the execution of a system in order to minimize its state space for efficient verification of temporal logic properties. This paper presents a framework for concisely defining and evaluating symmetry reductions currently used in software model checking, involving heap objects and processes. An on-the-fly state space exploration algorithm combining both techniques will also be presented. Second, the relation between symmetry and partial-order reductions is investigated, showing how ones strengths can be used to compensate for the others weaknesses. The symmetry reductions presented here were implemented in the dSPIN model-checking tool. We also performed a number of experiments that show significant progress in reducing the cost of finite-state software verification.     

激光间接驱动对称性分析的GPU并行求解

在激光间接驱动惯性约束聚变(ICF)辐射对称性分析中,当靶表面网格离散细密时,面元辐射能流计算耗时长,严重制约实验设计仿真及优化的快速开展,针对上述问题提出了基于GPU的并行计算方法,在CUDA架构下,通过网格单元视角因子计算过程到GPU各运算线程的映射,结合雅可比迭代法求解系数矩阵对角占优方程组快速收敛的特点,实现了对ICF分析模型靶表面辐射能流的高效计算.以三维仿真软件IRAD3D为平台,神光-Ⅱ激光装置和神光-Ⅲ原型装置的两个实验靶模型为案例,实验结果表明,改进方法能够充分利用GPU的硬件特性,对称性分析和参数优化的加速比在1000左右,大大提高了实验设计的效率.     

Symmetry,beauty and chaos in Chebyshev's paradise

Chebyshev polynomials and Halley maps are used as a reservoir for the generation of several visually striking and intricate classes of symmetrical and chaotic patterns. Relatively simple numerical recipes are included to encourage reader involvement.     

Emergence of multiagent spatial coordination strategies through artificial coevolution

This paper describes research investigating the evolution of coordination strategies in robot soccer teams. Each player (viewed as an agent) is provided with a common set of skills and is assigned to perform over a delimited area inside a soccer field. The idea is to optimize the whole team behavior by means of a spatial coadaptation process in which new players are selected in such a way to comply with the already existing ones. The main results show that, through coevolution, we progressively create teams whose members act on complementary areas of the playing field, being capable of prevailing over a standard opponent team with a fixed formation.     

基于声辐射模态的作动器对称位置的研究

在汽车噪声优化控制领域中,作动器位置布置会影响噪声控制效果。以简支板为例,根据声辐射模态的解耦主动控制的控制方法已经取得了良好的降噪效果,但作动器的不同对称位置布置对降噪产生的效果以及所需电压值是不同的。提出将分别对前四阶声辐射模态建立电压模型,对前八阶声辐射模态建立声功率模型,通过在MATLAB上进行仿真,结果确定能使所需电压最小,控制效果最好的理想降噪对称位置。     

Opportunities for multiagent systems and multiagent reinforcement learning in traffic control

The increasing demand for mobility in our society poses various challenges to traffic engineering, computer science in general, and artificial intelligence and multiagent systems in particular. As it is often the case, it is not possible to provide additional capacity, so that a more efficient use of the available transportation infrastructure is necessary. This relates closely to multiagent systems as many problems in traffic management and control are inherently distributed. Also, many actors in a transportation system fit very well the concept of autonomous agents: the driver, the pedestrian, the traffic expert; in some cases, also the intersection and the traffic signal controller can be regarded as an autonomous agent. However, the “agentification” of a transportation system is associated with some challenging issues: the number of agents is high, typically agents are highly adaptive, they react to changes in the environment at individual level but cause an unpredictable collective pattern, and act in a highly coupled environment. Therefore, this domain poses many challenges for standard techniques from multiagent systems such as coordination and learning. This paper has two main objectives: (i) to present problems, methods, approaches and practices in traffic engineering (especially regarding traffic signal control); and (ii) to highlight open problems and challenges so that future research in multiagent systems can address them.     

Design and testing of a low-cost robotic wheelchair prototype

Many people who are mobility impaired are, for a variety of reasons, incapable of using an ordinary wheelchair. In some instances, a power wheelchair also cannot be used, usually because of the difficulty the person has in controlling it (often due to additional disabilities). This paper describes two low-cost robotic wheelchair prototypes that assist the operator of the chair in avoiding obstacles, going to pre-designated places, and maneuvering through doorways and other narrow or crowded areas. These systems can be interfaced to a variety of input devices, and can give the operator as much or as little moment by moment control of the chair as they wish. This paper describes both systems, the evolution from one system to another, and the lessons learned.     

Teamwork in multi-person systems: a review and analysis

As the scope and complexity of modern task demands exceed the capability of individuals to perform, teams are emerging to shoulder the burgeoning requirements. Accordingly, researchers have striven to understand and enhance human performance in team settings. The purpose of this review is to summarize that research, from the theoretical underpinnings that drive it, to the identification of team-level elements of success, to the methodologies and instruments that capture and measure those characteristics. Further specified are three important avenues to creating successful teams: team selection, task design and team training. In other words, one can select the right people, provide them with a task engineered for superior performance and train them in the appropriate skills to accomplish that task. Under task design, new technologies and automation are examined that both support and impede team functioning. Finally, throughout are provided critical remarks about what is known about teamwork and what is needed to be known to move the science and practice of team performance forward. The paper concludes with the identification of team issues that require further investigation.     

Compound behaviors in pheromone robotics

We are pursuing techniques for coordinating the actions of large numbers of small-scale robots to achieve useful large-scale results in surveillance, reconnaissance, hazard detection, and path finding. Using the biologically inspired notion of “virtual pheromone” messaging, we describe how many coordinated activities can be accomplished without centralized control. By virtue of this simple messaging scheme, a robot swarm can become a distributed computing mesh embedded within the environment, while simultaneously acting as a physical embodiment of the user interface. We further describe a set of logical primitives for controlling the flow of virtual pheromone messages throughout the robot swarm. These enable the design of complex group behaviors mediated by messages exchanged between neighboring robots.     

机器人行为选择机制综述

详细综述了现有的机器人行为选择方法及国内外研究现状,并讨论了行为选择机制研究发展的趋势,特别对受生物启发的机器人行为选择机制作了重点介绍．文章最后分析了机器人行为选择研究存在的问题并对以后的研究方向作了展望．     

Cognitive diversity and team performance in a complex multiple task environment

This article examines the multiple effects of cognitive diversity in teams operating complex human-machine-systems. The study employed a PC-based multiple-task environment, called the Cabin Air Management System, which models a process control task in the operational context of a spacecraft's life support system. Two types of cognitive diversity were examined: system understanding and team specialization. System understanding referred to the depth of understanding team members were given during training (low-level procedure-oriented vs. high level knowledge-oriented training). Team specialization referred to the degree to which knowledge about system fault scenarios was distributed between team members (specialized vs. non-specialized). A total of 72 participants took part in the study. After having received 4.5 h of training on an individual basis, participants completed a 1-h experimental session, in which they worked in two-person teams on a series of fault scenarios of varying difficulty. Measures were taken of primary and secondary task performance, system intervention and information sampling strategies, system knowledge, subjective operator state, communication patterns and conflict. The results provided evidence for the benefits of cognitive diversity with regard to system understanding. This manifested itself in better primary task performance and more efficient manual system control. No advantages were found for cognitive diversity with regard to specialization. There was no effect of cognitive diversity on intra-team conflict, with conflict levels generally being very low. The article concludes with a discussion of the implications of the findings for the engineering of cognitive diversity in teams operating complex human-machine-systems.