An introduction to swarm robotics

Swarm robotics is a field of multi-robotics in which large number of robots are coordinated in a distributed and decentralised way. It is based on the use of local rules, and simple robots compared to the complexity of the task to achieve, and inspired by social insects. Large number of simple robots can perform complex tasks in a more efficient way than a single robot, giving robustness and flexibility to the group. In this article, an overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems. A review of different research works and experimental results, together with a discussion of the future swarm robotics in real world applications completes this work.

A cooperative multi-agent robotics system: design and modelling

This paper presents the development of the robotic multi-agent system SMART. In this system, the agent concept is applied to both hardware and software entities. Hardware agents are robots, with three and four legs, and an IP-camera that takes images of the scene where the cooperative task is carried out. Hardware agents strongly cooperate with software agents. These latter agents can be classified into image processing, communications, task management and decision making, planning and trajectory generation agents. To model, control and evaluate the performance of cooperative tasks among agents, a kind of PetriNet, called Work-Flow Petri Net, is used. Experimental results shows the good performance of the system.

Probabilistic meta-analysis of risk from the exposure to Hg in artisanal gold mining communities in Colombia

Colombia is one of the largest per capita mercury polluters in the world as a consequence of its artisanal gold mining activities. The severity of this problem in terms of potential health effects was evaluated by means of a probabilistic risk assessment carried out in the twelve departments (or provinces) in Colombia with the largest gold production. The two exposure pathways included in the risk assessment were inhalation of elemental Hg vapors and ingestion of fish contaminated with methyl mercury. Exposure parameters for the adult population (especially rates of fish consumption) were obtained from nation-wide surveys and concentrations of Hg in air and of methyl-mercury in fish were gathered from previous scientific studies. Fish consumption varied between departments and ranged from 0 to 0.3 kg d?1. Average concentrations of total mercury in fish (70 data) ranged from 0.026 to 3.3 lg g?1. A total of 550 individual measurements of Hg in workshop air (ranging from menor queDL to 1 mg m?3) and 261 measurements of Hg in outdoor air (ranging from menor queDL to 0.652 mg m?3) were used to generate the probability distributions used as concentration terms in the calculation of risk. All but two of the distributions of Hazard Quotients (HQ) associated with ingestion of Hg-contaminated fish for the twelve regions evaluated presented median values higher than the threshold value of 1 and the 95th percentiles ranged from 4 to 90. In the case of exposure to Hg vapors, minimum values of HQ for the general population exceeded 1 in all the towns included in this study, and the HQs for miner-smelters burning the amalgam is two orders of magnitude higher, reaching values of 200 for the 95th percentile. Even acknowledging the conservative assumptions included in the risk assessment and the uncertainties associated with it, its results clearly reveal the exorbitant levels of risk endured not only by miner-smelters but also by the general population of artisanal gold mining communities in Colombia.

Probabilistic approach for longitudinal ventilation system design in fire situations

The main objective of ventilation systems in tunnels is to reach the highest possible safety level both in service and fire situation; being the fire one, the most relevant when designing the system. When designing a longitudinal ventilation system, the methodology to evaluate the capacity of the system is similar both in service and fire situation, with the exception of the chimney effect and the phenomena of thermal transfer which is responsible or the changes in the density of the air. When facing the dimensioning task for longitudinal ventilated tunnels, although similar methodologies are used in different countries, specific hypothesis (aerodynamic, thermal properties, traffic) even if discussed in the literature or current practice, are not usually detailed in the regulations or recommendations. The aim of this paper is to propose a probabilistic approach to the problem which would allow the designer, and the tunnel owner, to understand the uncertainty and sensibility adopted in the results and, eventually, identify possible ways of optimizing the ventilation solution to be adopted.

A dynamic, probabilistic model for city building

The problem of interdependence between housing and commuting in a city has been analysed within the framework of welfare economics. Uncertain changes overtime in the working population has been considered by means of a dynamic, probabilistic model. The characteristics of irreversibility and durability in city building have been explicitly dealt with. The ultimate objective is that the model after further development will be an auxiliary tool in city planning.

Probabilistic assessment of risk from the exposure to mercury in artisanal gold mining communities in Colombia

Colombia is one the largest per capita mercury polluters as a consequence of its artisanal gold mining operations, which are steadily increasing following the rising price of this metal. Compared to gravimetric separation methods and cyanidation, the concentration of gold using Hg amalgams presents several advantages: the process is less time-consuming and minimizes gold losses, and Hg is easily transported and inexpensive relative to the selling price of gold. Very often, mercury amalgamation is carried out on site by unprotected workers. During this operation large amounts of mercury are discharged to the environment and eventually reach the fresh water bodies in the vicinity where it is subjected to methylation. Additionally, as gold is released from the amalgam by heating on open charcoal furnaces in small workshops, mercury vapors are emitted and inhaled by the artisanal smelters and the general population

Integrated deterministic-probabilistic safety assessment methodologies

(ENG) IDPSA (Integrated Deterministic-Probabilistic Safety Assessment) is a family of methods which use tightly coupled probabilistic and deterministic approaches to address respective sources of uncertainties, enabling Risk informed decision making in a consistent manner. The starting point of the IDPSA framework is that safety justification must be based on the coupling of deterministic (consequences) and probabilistic (frequency) considerations to address the mutual interactions between stochastic disturbances (e.g. failures of the equipment, human actions, stochastic physical phenomena) and deterministic response of the plant (i.e. transients). This paper gives a general overview of some IDPSA methods as well as some possible applications to PWR safety analyses (SPA)DPSA (Metodologías Integradas de Análisis Determinista-Probabilista de Seguridad) es un conjunto de métodos que utilizan métodos probabilistas y deterministas estrechamente acoplados para abordar las respectivas fuentes de incertidumbre, permitiendo la toma de decisiones Informada por el Riesgo de forma consistente. El punto de inicio del marco IDPSA es que la justificación de seguridad debe estar basada en el acoplamiento entre consideraciones deterministas (consecuencias) y probabilistas (frecuencia) para abordar la interacción mutua entre perturbaciones estocásticas (como por ejemplo fallos de los equipos, acciones humanas, fenómenos físicos estocásticos) y la respuesta determinista de la planta (como por ejemplo los transitorios). Este artículo da una visión general de algunos métodos IDSPA así como posibles aplicaciones al análisis de seguridad de los PWR.

Quantifying dispersal paths in probabilistic habitat networks: a reply to hock and mumby (2015) and an overview of recent developments and applications

Hock and Mumby (2015) describe an approach to quantify dispersal probabilities along paths in networks of habitat patches. This approach basically consists in determining the most probable (most reliable) path for movement between habitat patches by calculating the product of the dispersal probabilities in each link (step) along the paths in the network. Although the paper by Hock and Mumby (2015) has value and includes interesting analyses (see comments in section 7 below), the approach they describe is not new.

Multi-sensor background subtraction by fusing multiple region-based probabilistic classifiers

In the recent years, the computer vision community has shown great interest on depth-based applications thanks to the performance and flexibility of the new generation of RGB-D imagery. In this paper, we present an efficient background subtraction algorithm based on the fusion of multiple region-based classifiers that processes depth and color data provided by RGB-D cameras. Foreground objects are detected by combining a region-based foreground prediction (based on depth data) with different background models (based on a Mixture of Gaussian algorithm) providing color and depth descriptions of the scene at pixel and region level. The information given by these modules is fused in a mixture of experts fashion to improve the foreground detection accuracy. The main contributions of the paper are the region-based models of both background and foreground, built from the depth and color data. The obtained results using different database sequences demonstrate that the proposed approach leads to a higher detection accuracy with respect to existing state-of-the-art techniques.

Class-Conditional Probabilistic Principal Component Analysis: application to gender recognition

Este trabajo presenta una solución al problema del reconocimiento del género de un rostro humano a partir de una imagen. Adoptamos una aproximación que utiliza la cara completa a través de la textura de la cara normalizada y redimensionada como entrada a un clasificador Näive Bayes. Presentamos la técnica de Análisis de Componentes Principales Probabilístico Condicionado-a-la-Clase (CC-PPCA) para reducir la dimensionalidad de los vectores de características para la clasificación y asegurar la asunción de independencia para el clasificador. Esta nueva aproximación tiene la deseable propiedad de presentar un modelo paramétrico sencillo para las marginales. Además, este modelo puede estimarse con muy pocos datos. En los experimentos que hemos desarrollados mostramos que CC-PPCA obtiene un 90% de acierto en la clasificación, resultado muy similar al mejor presentado en la literatura---ABSTRACT---This paper presents a solution to the problem of recognizing the gender of a human face from an image. We adopt a holistic approach by using the cropped and normalized texture of the face as input to a Naïve Bayes classifier. First it is introduced the Class-Conditional Probabilistic Principal Component Analysis (CC-PPCA) technique to reduce the dimensionality of the classification attribute vector and enforce the independence assumption of the classifier. This new approach has the desirable property of a simple parametric model for the marginals. Moreover this model can be estimated with very few data. In the experiments conducted we show that using CCPPCA we get 90% classification accuracy, which is similar result to the best in the literature. The proposed method is very simple to train and implement.

A Survey on Intermediation Architectures for Underwater Robotics

Currently, there is a plethora of solutions regarding interconnectivity and interoperability for networked robots so that they will fulfill their purposes in a coordinated manner. In addition to that, middleware architectures are becoming increasingly popular due to the advantages that they are capable of guaranteeing (hardware abstraction, information homogenization, easy access for the applications above, etc.). However, there are still scarce contributions regarding the global state of the art in intermediation architectures for underwater robotics. As far as the area of robotics is concerned, this is a major issue that must be tackled in order to get a holistic view of the existing proposals. This challenge is addressed in this paper by studying the most compelling pieces of work for this kind of software development in the current literature. The studied works have been assessed according to their most prominent features and capabilities. Furthermore, by studying the individual pieces of work and classifying them several common weaknesses have been revealed and are highlighted. This provides a starting ground for the development of a middleware architecture for underwater robotics capable of dealing with these issues.

Robotic control systems based on bioinspired multi-agent systems: application of the principles of neuroscience to robotics

Robotics is a field that presents a large number of problems because it depends on a large number of disciplines, devices, technologies and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges, such as robots household robots or professional robots. To facilitate the rapid development of robotic systems, low cost, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems.

A combined probabilistic framework for learning gestures and actions

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.

Learning Probabilistic Features for Robotic Navigation Using Laser Sensors

SLAM is a popular task used by robots and autonomous vehicles to build a map of an unknown environment and, at the same time, to determine their location within the map. This paper describes a SLAM-based, probabilistic robotic system able to learn the essential features of different parts of its environment. Some previous SLAM implementations had computational complexities ranging from O(Nlog(N)) to O(N2), where N is the number of map features. Unlike these methods, our approach reduces the computational complexity to O(N) by using a model to fuse the information from the sensors after applying the Bayesian paradigm. Once the training process is completed, the robot identifies and locates those areas that potentially match the sections that have been previously learned. After the training, the robot navigates and extracts a three-dimensional map of the environment using a single laser sensor. Thus, it perceives different sections of its world. In addition, in order to make our system able to be used in a low-cost robot, low-complexity algorithms that can be easily implemented on embedded processors or microcontrollers are used.

Behaviours, Processes and Probabilistic Environmental Functions in H-Open Systems

The Patten’s Theory of the Environment, supposes an impotent contribution to the Theoretical Ecology. The hypothesis of the duality of environments, the creaon and genon functions and the three developed propositions are so much of great importance in the field of the Applied Mathematical as Ecology. The authors have undertaken an amplification and revision of this theory, developing the following steps: 1) A theory of processes. 2) A definition of structural and behavioural functions. 3) A probabilistic definition of the environmental functions. In this paper the authors develop the theory of behavioural functions, begin the theory of environmental functions and give a complementary focus to the theory of processes that has been developed in precedent papers.