Redundant Sensors for Mobile Robot Navigation

Redundant sensors are needed on a mobile robot so that the accuracy with which it perceives its surroundings can be increased. Sonar and infrared sensors are used here in tandem, each compensating for deficiencies in the other. The robot combines the data from both sensors to build a representation which is more accurate than if either sensor were used alone. Another representation, the curvature primal sketch, is extracted from this perceived workspace and is used as the input to two path planning programs: one based on configuration space and one based on a generalized cone formulation of free space.

Prices versus quantities versus bankable quantities

Quantity-based regulation with banking allows regulated firms to shift obligations across time in response to periods of unexpectedly high or low marginal costs. Despite its wide prevalence in existing and proposed emission trading programs, banking has received limited attention in past welfare analyses of policy choice under uncertainty. We address this gap with a model of banking behavior that captures two key constraints: uncertainty about the future from the firm's perspective and a limit on negative bank values (e.g. borrowing). We show conditions where banking provisions reduce price volatility and lower expected costs compared to quantity policies without banking. For plausible parameter values related to U.S. climate change policy, we find that bankable quantities produce behavior quite similar to price policies for about two decades and, during this period, improve welfare by about a $1 billion per year over fixed quantities. © 2012 Elsevier B.V.

Safeguarding: A case for intelligent risk management

‘Risk’ in social work is typically read as risk-of-bads, and specifically extreme bads. This paper develops the implications of the logical objection to attempts to predict low frequency extreme events (such as child homicides). Our argument is that if we focus on these low probability high cost outcomes—these heart wrenching, but unpredictable, tragedies—we take social work away from the good that it can do, leave it open to inappropriate disapprobation, and, in terms of outcomes, do less well by the vulnerable. This point is reinforced by discussion of developments in other academic fields, and by further examination of the logic (and the morality) of protection under uncertainty. We explore the implications for the way social work should be evaluated. A proper academic understanding of risk, and decision making under uncertainty, has, we argue clear practical implications.

COLREGs-based collision avoidance strategies for unmanned surface vehicles

The aim of this paper is to report the preliminary development of an automatic collision avoidance technique for unmanned marine craft based on standardised rules, COLREGs, defined by the International Maritime Organisation. It is noted that all marine surface vessels are required to adhere to COLREGs at all times in order to minimise or eliminate the risk of collisions. The approach presented is essentially a reactive path planning algorithm which provides feedback to the autopilot of an unmanned vessel or the human captain of a manned ship for steering the craft safely. The proposed strategy consists of waypoint guidance by line-of-sight coupled with a manual biasing scheme. This is applied to the dynamic model of an unmanned surface vehicle. A simple PID autopilot is incorporated to ensure that the vessel adheres to the generated seaway. It is shown through simulations that the resulting scheme is able to generate viable trajectories in the presence of both stationary and dynamic obstacles. Rules 8 and 14 of the COLREGs, which apply to the amount of manoeuvre and to a head-on scenario respectively are simulated. A comparison is also made with an offline or deliberative grid-based path planning algorithm which has been modified to generate COLREGs-compliant routes.

An intelligent configuration-sampling based local motion planner for robotic manipulators

Manipulator motion planning is a task which relies heavily on the construction of a configuration space prior to path planning. However when fast real-time motion is needed, the full construction of the manipulator's high-dimensional configu-ration space can be too slow and expensive. Alternative planning methods, which avoid this full construction of the manipulator's configuration space are needed to solve this problem. Here, one such existing local planning method for manipulators based on configuration-sampling and subgoal-selection has been extended. Using a modified Artificial Potential Fields (APF) function, goal-configuration sampling and a novel subgoal selection method, it provides faster, more optimal paths than the previously proposed work. Simulation results show a decrease in both runtime and path lengths, along with a decrease in unexpected local minimum and crashing issues.

An automatic COLREGs-compliant obstacle avoidance system for an unmanned surface vehicle

Unmanned surface vehicles are becoming increasingly vital tools in a variety of maritime applications. Unfortunately, their usability is severely constrained by the lack of a reliable obstacle detection and avoidance system. In this article, one such experimental platform is proposed, which performs obstacle detection, risk assessment and path planning (avoidance) tasks autonomously in an integrated manner. The detection system is based on a vision-LIDAR (light detection and ranging) system, whereas a heuristic path planner is utilised. A unique property of the path planner is its compliance with the marine collision regulations. It is demonstrated through hardware-in-the-loop simulations that the proposed system can be useful for both uninhabited and manned vessels.

Compromising Spatial Quality: Modernity in the Era of National State Building in Cairo

The paper examines the imposition of western ideals of urbanism within colonial Cairo between1882-1952. It looks at the ideologies of capitalism, state control, and utopian idealism, which were vital tools to create modern built environments in the city. The argument is that principles of Western urbanism were at work and deeply influenced the institutional and professional practices of the Egyptian planners, who were mostly educated in Europe; however the outcomes revealed a major shift towards more inflexible solutions described as more open to compromise with the existing conditions. The paper analyses the case of a re-planning scheme drafted in the 1920s by the first Egyptian director of the Ministry of Town Planning under the British occupation. The scheme represented the superimposition of a western-style neighbourhood model on a historically rooted traditional quarter in Cairo. The paper largely relies on original archival materials, maps, documents and accounts to support the historical narrative of urban planning in Cairo. It reports that westernization approaches for planning Cairo were introduced to offer a new imagery representation, which remained central to the development of planning practices in postcolonial Egypt through different practical applications.

An Intelligent Threat Prevention Framework with Heterogeneous Information

Three issues usually are associated with threat prevention intelligent surveillance systems. First, the fusion and interpretation of large scale incomplete heterogeneous information; second, the demand of effectively predicting suspects’ intention and ranking the potential threats posed by each suspect; third, strategies of allocating limited security resources (e.g., the dispatch of security team) to prevent a suspect’s further actions towards critical assets. However, in the literature, these three issues are seldomly considered together in a sensor network based intelligent surveillance framework. To address
this problem, in this paper, we propose a multi-level decision support framework for in-time reaction in intelligent surveillance. More specifically, based on a multi-criteria event modeling framework, we design a method to predict the most plausible intention of a suspect. Following this, a decision support model is proposed to rank each suspect based on their threat severity and to determine resource allocation strategies. Finally, formal properties are discussed to justify our framework.

The Complexity of Approximately Solving Influence Diagrams

Influence diagrams allow for intuitive and yet precise description of complex situations involving decision making under uncertainty. Unfortunately, most of the problems described by influence diagrams are hard to solve. In this paper we discuss the complexity of approximately solving influence diagrams. We do not assume no-forgetting or regularity, which makes the class of problems we address very broad. Remarkably, we show that when both the treewidth and the cardinality of the variables are bounded the problem admits a fully polynomial-time approximation scheme.

Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.

Weak and strong disjunction in possibilistic ASP

Possibilistic answer set programming (PASP) unites answer set programming (ASP) and possibilistic logic (PL) by associating certainty values with rules. The resulting framework allows to combine both non-monotonic reasoning and reasoning under uncertainty in a single framework. While PASP has been well-studied for possibilistic definite and possibilistic normal programs, we argue that the current semantics of possibilistic disjunctive programs are not entirely satisfactory. The problem is twofold. First, the treatment of negation-as-failure in existing approaches follows an all-or-nothing scheme that is hard to match with the graded notion of proof underlying PASP. Second, we advocate that the notion of disjunction can be interpreted in several ways. In particular, in addition to the view of ordinary ASP where disjunctions are used to induce a non-deterministic choice, the possibilistic setting naturally leads to a more epistemic view of disjunction. In this paper, we propose a semantics for possibilistic disjunctive programs, discussing both views on disjunction. Extending our earlier work, we interpret such programs as sets of constraints on possibility distributions, whose least specific solutions correspond to answer sets.

Changing climate, changing decisions : understanding climate adaptation decision-making and the way science supports it

Tese de doutoramento, Ciências do Ambiente, Universidade de Lisboa, Faculdade de Ciências, Universidade Nova de Lisboa, 2015

Planeamento de Trajetória para Operações de Busca e Salvamento com UAVs

Os sistemas autónomos trazem como mais valia aos cenários de busca e salvamento a possibilidade de minimizar a presença de Humanos em situações de perigo e a capacidade de aceder a locais de difícil acesso. Na dissertação propõe-se endereçar novos métodos para perceção e navegação de veículos aéreos não tripulados (UAV), tendo como foco principal o planeamento de trajetórias e deteção de obstáculos. No que respeita à perceção foi desenvolvido um método para gerar clusters tendo por base os voxels gerados pelo Octomap. Na área de navegação, foram desenvolvidos dois novos métodos de planeamento de trajetórias, GPRM (Grid Probabilistic Roadmap) e PPRM (Particle Probabilistic Roadmap), que tem como método base para o seu desenvolvimento o PRM. O primeiro método desenvolvido, GPRM, espalha as partículas numa grid pré-definida, construindo posteriormente o roadmap na área determinada pela grid e com isto estima o trajeto mais curto até ao ponto destino. O segundo método desenvolvido, PPRM, espalha as partículas pelo cenário de aplicação, gera o roadmap considerando o mapa total e atribui uma probabilidade que irá permitir definir a trajetória otimizada. Para analisar a performance de cada método em comparação com o PRM, efetua-se a sua avaliação em três cenários distintos com recurso ao simulador MORSE.

Efficiency in Uncertain Cooperative Games

A contingent contract in a transferable utility game under uncertainty specifies an outcome for each possible state. It is assumed that coalitions evaluate these contracts by considering the minimal possible excesses. A main question of the paper concerns the existence and characterization of efficient contracts. It is shown that they exist if and only if the set of possible coalitions contains a balanced subset. Moreover, a characterization of values that result in efficient contracts in the case of minimally balanced collections is provided.

Harsanyi’s Social Aggregation Theorem : A Multi-Profile Approach with Variable-Population Extensions

This paper provides new versions of Harsanyi’s social aggregation theorem that are formulated in terms of prospects rather than lotteries. Strengthening an earlier result, fixed-population ex-ante utilitarianism is characterized in a multi-profile setting with fixed probabilities. In addition, we extend the social aggregation theorem to social-evaluation problems under uncertainty with a variable population and generalize our approach to uncertain alternatives, which consist of compound vectors of probability distributions and prospects.