Optimal Camera Placement for Automated Surveillance Tasks

Camera placement has an enormous impact on the performance of vision systems, but the best placement to maximize performance depends on the purpose of the system. As a result, this paper focuses largely on the problem of task-specific camera placement. We propose a new camera placement method that optimizes views to provide the highest resolution images of objects and motions in the scene that are critical for the performance of some specified task (e.g. motion recognition, visual metrology, part identification, etc.). A general analytical formulation of the observation problem is developed in terms of motion statistics of a scene and resolution of observed actions resulting in an aggregate observability measure. The goal of this system is to optimize across multiple cameras the aggregate observability of the set of actions performed in a defined area. The method considers dynamic and unpredictable environments, where the subject of interest changes in time. It does not attempt to measure or reconstruct surfaces or objects, and does not use an internal model of the subjects for reference. As a result, this method differs significantly in its core formulation from camera placement solutions applied to problems such as inspection, reconstruction or the Art Gallery class of problems. We present tests of the system’s optimized camera placement solutions using real-world data in both indoor and outdoor situations and robot-based experimentation using an all terrain robot vehicle-Jr robot in an indoor setting.     

Stability and Constitutive Modelling in Multiphase TRIP Steels

Multiphase TRIP steels are a relatively new class of steels exhibiting excellent combinations of strength and cold formability, a fact that renders them particularly attractive for automotive applications. The present work reports models regarding the prediction of the stability of retained austenite, the optimisation of the heat‐treatment stages necessary for austenite stabilization in the microstructure, as well as the mechanical behaviour of these steels under deformation. Austenite stability against mechanically‐induced transformation to martensite depends on chemical composition, austenite particle size, strength of the matrix and stress state. The stability of retained austenite is characterized by the M^σ_S temperature, which can be expressed as a function of the aforementioned parameters by an appropriate model presented in this work. Besides stability, the mechanical behaviour of TRIP steels also depends on the amount of retained austenite present in the microstructure. This amount is determined by the combinations of temperature and temporal duration of the heat‐treatment stages undergone by the steel. Maximum amounts of retained austenite require optimisation of the heat‐treatment conditions. A physical model is presented in this work, which is based on the interactions between bainite and austenite during the heat‐treatment of multiphase TRIP steels, and which allows for the selection of treatment conditions leading to the maximization of retained austenite in the final microstructure. Finally, a constitutive micromechanical model is presented, which describes the mechanical behaviour of multiphase TRIP steels under deformation, taking into account the different plastic behaviour of the individual phases, as well as the evolution of the microstructure itself during plastic deformation. This constitutive micromechanical model is subsequently used for the calculation of forming limit diagrams (FLD) for these complex steels, an issue of great practical importance for the optimisation of stretch‐forming and deep‐drawing operations.     

Assembling Colloidal Silica into Porous Hollow Microspheres

A non-surfactant-based synthesis approach to mesoporous hollow spheres through the use of colloidal silica is presented. Based on nanoparticle assembly chemistry developed previously for silica/polymer hybrid microcapsules, the room-temperature preparation follows a two-step sequence: (1) the electrostatic reaction of cationic polymer with an anionic salt solution, resulting in a suspension of salt-bridged polymer aggregates; and (2) the electrostatic reaction between this suspension and an aqueous suspension of nanoparticles (NPs). As a specific example, 13-nm silica particles, combined with polyallylamine and sodium citrate, gave silica/polymer hollow spheres with a mean diameter of 2.1 μm and a BET surface area of 4 m²/g. After calcination at 600 °C, the resulting silica-only microcapsules had a BET surface area of 259 m²/g, a modal pore size of 4.0 nm, and a pore volume of 0.38 cc/g, values that exceeded those of calcined silica NPs. This colloidal silica-based material is an example of the simultaneous control of pore size (at the nanometer scale) and particle morphology (at the micrometer scale) that is possible through charge-driven NP assembly.     

Construction of invariant polytopic sets with specified complexity

The problem of construction of controlled invariant polytopic sets with specified complexity, for linear systems subject to linear state and control constraints, is investigated. First, geometric conditions for the enlargement of a polytopic set by adding a new vertex, in order to produce a polytopic set of specified complexity, are established. Next, conditions for such an enlargement of controlled invariant sets to preserve the controlled invariance property are presented. The established theoretical results are used to develop methods for the construction of admissible controlled invariant sets with specified complexity. Two numerical examples show how these results can be used for the computation of monotonic sequences of admissible controlled invariant sets of specified complexity.     

Nonlinear stabilization in infinite dimension

Significant advances have taken place in the last few years in the development of control designs for nonlinear infinite-dimensional systems. Such systems typically take the form of nonlinear ODEs (ordinary differential equations) with delays and nonlinear PDEs (partial differential equations). In this article we review several representative but general results on nonlinear control in the infinite-dimensional setting. First we present designs for nonlinear ODEs with constant, time-varying or state-dependent input delays, which arise in numerous applications of control over networks. Second, we present a design for nonlinear ODEs with a wave (string) PDE at its input, which is motivated by the drilling dynamics in petroleum engineering. Third, we present a design for systems of (two) coupled nonlinear first-order hyperbolic PDEs, which is motivated by slugging flow dynamics in petroleum production in off-shore facilities. Our design and analysis methodologies are based on the concepts of nonlinear predictor feedback and nonlinear infinite-dimensional backstepping. We present several simulation examples that illustrate the design methodology.     

An SPN-Neural Planning Methodology for Coordination of two Robotic Hands with Constrained Placement

This paper presents a planning methodology based on Stochastic Petri Nets (SPNs) and Neural nets for coordination of two robotic arms working in a space with constrained placement. The SPN planning method generates a global plan based on the states of the elements of the Universe of Discourse. The plan includes all the possible conflict-free planning paths to achieve the goals under constraints, such as specific locations on which objects have to be placed, order of placement, etc. An associated neural network is used to search the vectors of markings generated by the SPN reachability graph for the appropriate selection of plans. Moreover, it preserves all the interesting features of the SPN model, such as synchronization, parallelism, concurrency and timing of events. The coordination of two robotic arms is used as an illustrative example for the proposed planning method, in a UD space where the location of objects placement are restricted.     

Ancient Roman nano-technology: Insight into the manufacture of mosaic tesserae opacified by calcium antimonate

Opaque mosaic glass tesserae containing calcium antimonates from Ancient Messene, Greece (1st–4th century CE) were investigated by scanning electron microscopy, Raman spectroscopy and X-ray diffraction. Both trigonal CaSb₂O₆ and cubic Ca₂Sb₂O₇, with crystallite diameters below 1?μm, were identified as opacifying agents. To better understand ancient technologies, we prepared model glasses that were opacified by crystallisation via a secondary heat treatment, by direct crystallisation during the melting process, or by the addition of pre-reacted calcium antimonate to a base glass. We found that direct crystallisation replicated the antique glass artefacts most accurately.We demonstrated that 0.2?wt% of nucleating agents like TiO₂ and SnO₂ already exert significant influence on the crystallisation behaviour of calcium antimonates. Secondary scattering centres such as silica and carbonates contribute to the optical appearance. Concurrently, we reproduced opaque white glass ceramics in a reconstructed, wood-fired, Roman-type glass furnace built by Wiesenberg (2014).