It was the end of the century, or rather the millennium. We were in the large lecture hall of the Technical University of Stuttgart, in Keplerstra?e. Many were the participants in one of the last biennial “Photogrammetrische Woche”, governed by Carl Zeiss since the beginning.
Next to me was Friedrich Ackermann, who until 1992 had been director of the Institute of Photogrammetry and was now happily retired.
We had been on first name terms (duzen, in German) ever since he had been a guest of Professor Luigi Mussio and myself at the Milan Polytechnic (I talk about it in my little book “Topografi e fotogrammetri fra cronaca e storia”, published by Maggioli. “Fritz” was two years younger than me). There was a new speaker on the stage and suddenly a kind of toy with propeller
engines rose into the air, a real but very small helicopter, to the amazement of those present but not of Fritz who was well aware of it.
Proportional-Integral-Differential (PID) control is widely used in industrial control systems. However, up to now there are at least two open problems related with PID control. One is to have a comprehensive understanding of its robustness with respect to model uncertainties and disturbances. The other is to build intuitive, explicit and mathematically provable guidelines for PID gain tuning. In this paper, we introduce a simple nonlinear mapping to determine PID gains from three auxiliary parameters. By the mapping, PID control is shown to be equivalent to a new PD control (serving as a nominal control) plus an uncertainty and disturbance compensator (to recover the nominal performance). Then PID control can be understood, designed and tuned in a Two-Degree-of-Freedom (2-DoF) control framework. We discuss some basic properties of the mapping, including the existence, uniqueness and invertibility. Taking as an example the PID control applied to a general uncertain second-order plant, we prove by the singular perturbation theory that the closed-loop steady-state and transient performance depends explicitly on one auxiliary parameter which can be viewed as the virtual singular perturbation parameter (SPP) of PID control. All the three PID gains are monotonically decreasing functions of the SPP, indicating that the smaller the SPP is, the higher the PID gains are, and the better the robustness of PID control is. Simulation and experimental examples are provided to demonstrate the properties of the mapping as well as the effectiveness of the mapping based PID gain turning.
Process mapping asks to assign vertices of a task graph to processing elements of a supercomputer such that the computational workload is balanced while the communication cost is minimized. Motivated by the recent success of GPU-based graph partitioners, we propose two GPU-accelerated algorithms for this optimization problem. The first algorithm employs hierarchical multisection, which partitions the task graph alongside the hierarchy of the supercomputer. The method utilizes GPU-based graph partitioners to accelerate the mapping process. The second algorithm integrates process mapping directly into the modern multilevel graph partitioning pipeline. Vital phases like coarsening and refinement are accelerated by exploiting the parallelism of GPUs. The first algorithm has, on average, about 12 percent higher communication costs than the state-of-the-art solver and thus remains competitive with it. However, in terms of speed, it vastly outperforms the competitor with a geometric mean speedup of 22 times and a maximum speedup of 934 times. The second approach is even faster, with a geometric mean speedup of 1454 times and a peak speedup of 12376 times. Compared to other algorithms that prioritize speed over solution quality, this approach has the same quality but much greater speedups. To our knowledge, these are the first GPU-based algorithms for process mapping.
Javier Alejandro Chávez-Domínguez, Verónica Dimant, Daniel Galicer
We continue our study of the mapping ideal of operator $p$-compact maps, previously introduced by the authors. Our approach embraces a more geometric perspective, delving into the interplay between operator $p$-compact mappings and matrix sets, specifically we provide a quantitative notion of operator $p$-compactness for the latter. In particular, we consider operator $p$-compactness in the bidual and its relation with this property in the original space. Also, we deepen our understanding of the connections between these mapping ideals and other significant ones (e.g., completely $p$-summing, completely $p$-nuclear).
We present COMO, a real-time monocular mapping and odometry system that encodes dense geometry via a compact set of 3D anchor points. Decoding anchor point projections into dense geometry via per-keyframe depth covariance functions guarantees that depth maps are joined together at visible anchor points. The representation enables joint optimization of camera poses and dense geometry, intrinsic 3D consistency, and efficient second-order inference. To maintain a compact yet expressive map, we introduce a frontend that leverages the covariance function for tracking and initializing potentially visually indistinct 3D points across frames. Altogether, we introduce a real-time system capable of estimating accurate poses and consistent geometry.
Abhishek Goswami, Aru Ranjan Singh, Francesco Banterle
et al.
The range of real-world scene luminance is larger than the capture capability of many digital camera sensors which leads to details being lost in captured images, most typically in bright regions. Inverse tone mapping attempts to boost these captured Standard Dynamic Range (SDR) images back to High Dynamic Range (HDR) by creating a mapping that linearizes the well exposed values from the SDR image, and provides a luminance boost to the clipped content. However, in most cases, the details in the clipped regions cannot be recovered or estimated. In this paper, we present a novel inverse tone mapping approach for mapping SDR images to HDR that generates lost details in clipped regions through a semantic-aware diffusion based inpainting approach. Our method proposes two major contributions - first, we propose to use a semantic graph to guide SDR diffusion based inpainting in masked regions in a saturated image. Second, drawing inspiration from traditional HDR imaging and bracketing methods, we propose a principled formulation to lift the SDR inpainted regions to HDR that is compatible with generative inpainting methods. Results show that our method demonstrates superior performance across different datasets on objective metrics, and subjective experiments show that the proposed method matches (and in most cases outperforms) state-of-art inverse tone mapping operators in terms of objective metrics and outperforms them for visual fidelity.
Satellite technologies have great potential in cadastral works, significantly increasing the efficiency and accuracy of processes. The article examines the existing aspects of satellite monitoring for cadastral works and analyzes the issue of monitoring in the cadastre automation system related to the processing of information on cadastre objects. The basics of modern GIS technologies in conducting GPS satellite monitoring in the cadastre are described. Innovative programs for conducting satellite monitoring by other countries are considered. Which is especially relevant at the moment during military operations with the Russian Federation. Rapid monitoring using satellite technology will help increase the accuracy of reconnaissance and, accordingly, the effectiveness of artillery. The article analyzes the development of geodetic support during the performance of cadastral works, describes the use of the latest geodetic technologies - three-dimensional satellite scanning. The analysis of literary sources showed that there is a significant number of scientific works using satellite technologies for obtaining cadastral data and creating a three-dimensional cadastre. In which are described the methods of cadastral surveying, criteria for choosing measuring instruments, methods for assessing the accuracy of coordinates, algorithms for processing scanning data. However, the issue of further use of satellite technologies for cadastral documentation requires more detailed research.
Despite the increasing prevalence of robots in daily life, their navigation capabilities are still limited to environments with prior knowledge, such as a global map. To fully unlock the potential of robots, it is crucial to enable them to navigate in large-scale unknown and changing unstructured scenarios. This requires the robot to construct an accurate static map in real-time as it explores, while filtering out moving objects to ensure mapping accuracy and, if possible, achieving high-quality pedestrian tracking and collision avoidance. While existing methods can achieve individual goals of spatial mapping or dynamic object detection and tracking, there has been limited research on effectively integrating these two tasks, which are actually coupled and reciprocal. In this work, we propose a solution called S$^2$MAT (Simultaneous and Self-Reinforced Mapping and Tracking) that integrates a front-end dynamic object detection and tracking module with a back-end static mapping module. S$^2$MAT leverages the close and reciprocal interplay between these two modules to efficiently and effectively solve the open problem of simultaneous tracking and mapping in highly dynamic scenarios. We conducted extensive experiments using widely-used datasets and simulations, providing both qualitative and quantitative results to demonstrate S$^2$MAT's state-of-the-art performance in dynamic object detection, tracking, and high-quality static structure mapping. Additionally, we performed long-range robotic navigation in real-world urban scenarios spanning over 7 km, which included challenging obstacles like pedestrians and other traffic agents. The successful navigation provides a comprehensive test of S$^2$MAT's robustness, scalability, efficiency, quality, and its ability to benefit autonomous robots in wild scenarios without pre-built maps.
Elizabeth Field, Autumn Kent, Christopher Leininger
et al.
We provide a lower bound on the volume of the compactified mapping torus of a strongly irreducible end-periodic homeomorphism f. This result, together with work of Field, Kim, Leininger, and Loving, shows that the volume of the compactified mapping torus of f is comparable to the translation length of f on a connected component of the pants graph, extending work of Brock in the finite-type setting on volumes of mapping tori of pseudo-Anosov homeomorphisms.
Marking-level high-definition maps (HD maps) are of great significance for autonomous vehicles (AVs), especially in large-scale, appearance-changing scenarios where AVs rely on markings for localization and lanes for safe driving. In this paper, we propose a pose-guided optimization framework for automatically building a marking-level HD map with accurate markings positions using a simple sensor setup (one or more monocular cameras). We optimize the position of the marking corners to fit the result of marking segmentation and simultaneously optimize the inverse perspective mapping (IPM) matrix of the corresponding camera to obtain an accurate transformation from the front view image to the bird's-eye view (BEV). In the quantitative evaluation, the built HD map almost attains centimeter-level accuracy. The accuracy of the optimized IPM matrix is similar to that of the manual calibration. The method can also be generalized to build HD maps in a broader sense by increasing the types of recognizable markings. The supplementary materials and videos are available at http://liuhongji.site/V2HDM-Mono/.
In many autonomous mapping tasks, the maps cannot be accurately constructed due to various reasons such as sparse, noisy, and partial sensor measurements. We propose a novel map prediction method built upon the recent success of Low-Rank Matrix Completion. The proposed map prediction is able to achieve both map interpolation and extrapolation on raw poor-quality maps with missing or noisy observations. We validate with extensive simulated experiments that the approach can achieve real-time computation for large maps, and the performance is superior to the state-of-the-art map prediction approach - Bayesian Hilbert Mapping in terms of mapping accuracy and computation time. Then we demonstrate that with the proposed real-time map prediction framework, the coverage convergence rate (per action step) for a set of representative coverage planning methods commonly used for environmental modeling and monitoring tasks can be significantly improved.
Elizabeth Field, Priyam Patel, Alexander J. Rasmussen
We study stable commutator length on mapping class groups of certain infinite-type surfaces. In particular, we show that stable commutator length defines a continuous function on the commutator subgroups of such infinite-type mapping class groups. We furthermore show that the commutator subgroups are open and closed subgroups and that the abelianizations are finitely generated in many cases. Our results apply to many popular infinite-type surfaces with locally coarsely bounded mapping class groups.
In a period in which technology is advancing rapidly and even the national business plan (Industry 4.0) is pushing automation, the world of architecture is also changing. New technologies are mature. It is natural now to talk about BIM but what is the correct flow to transform a point cloud into a digital model that can be fully visited in VR? thanks to the use of the Autodesk platform you can take advantage of all the new technologies to achieve this: Infraworks can insert the project created with autodesk revit through three- dimensional maps. Once inserted the model can be animated and analyzed in its real context.
Dopo il D.M. 1444 del 1968 che ha introdotto gli standard urbanistici, ci si è interrogati
periodicamente sulla necessità di aggiornare l'insieme delle regole che determinano la costruzione degli spazi della città pubblica. Già 41 anni fa, le leggi urbanistiche regionali hanno cominciato a introdurre alcune specifiche al D.M. 1444. In particolare, dovendo decidere come rinunciare alla cessione di aree per standard urbanistici, le Regioni hanno introdotto l'istituto delle monetizzazioni.
Questo tema, seppur parte limitata di un più ampio e complesso dibattito sul rinnovamento e il coordinamento della normativa urbanistica nazionale, presenta una serie di criticità e opportunità teorico-operative su cui vale la pena soffermarsi. A partire da una analisi comparativa delle normative regionali italiane e da numerosi esempi applicativi dei comuni, il saggio si concentra soprattutto sul metodo di calcolo delle monetizzazioni e discute un caso studio innovativo che ha incluso nella computazione anche un principio di perequazione territoriale dei servizi che si basa sulla
quantificazione degli standard presenti nelle aree omogenee di Piano Regolatore. Sono stati utilizzati strumenti informativi territoriali con l'obiettivo di comprendere più efficacemente la distribuzione dei dati relativi agli standard nei luoghi in cui questi sono stati o saranno generati. Il metodo di calcolo proposto potrebbe permettere al decisore pubblico di utilizzare le monetizzazioni senza troppe discrezionalità e in modo più consapevole del semplice calcolo del valore immobiliare del terreno che oggi è largamente utilizzato in Italia.
We recently derived a spin-mapping approach for treating the nonadiabatic dynamics of a two-level system in a classical environment [J. Chem. Phys. 151, 044119 (2019)] based on the well-known quantum equivalence between a two-level system and a spin-1/2 particle. In the present paper, we generalize this method to describe the dynamics of $N$-level systems. This is done via a mapping to a classical phase space that preserves the $SU(N)$-symmetry of the original quantum problem. The theory reproduces the standard Meyer--Miller--Stock--Thoss Hamiltonian without invoking an extended phase space, and we thus avoid leakage from the physical subspace. In contrast with the standard derivation of this Hamiltonian, the generalized spin mapping leads to an $N$-dependent value of the zero-point energy parameter that is uniquely determined by the Casimir invariant of the $N$-level system. Based on this mapping, we derive a simple way to approximate correlation functions in complex nonadiabatic molecular systems via classical trajectories, and present benchmark calculations on the seven-state Fenna--Matthews--Olson complex. The results are significantly more accurate than conventional Ehrenfest dynamics, at a comparable computational cost, and can compete in accuracy with other state-of-the-art mapping approaches.
This paper presents a fully hardware synchronized mapping robot with support for a hardware synchronized external tracking system, for super-precise timing and localization. We also employ a professional, static 3D scanner for ground truth map collection. Three datasets are generated to evaluate the performance of mapping algorithms within a room and between rooms. Based on these datasets we generate maps and trajectory data, which is then fed into evaluation algorithms. The mapping and evaluation procedures are made in a very easily reproducible manner for maximum comparability. In the end we can draw a couple of conclusions about the tested SLAM algorithms.
Gary J. Mooney, Sam U. Y. Tonetto, Charles D. Hill
et al.
We introduce a framework for mapping NP-Hard problems to adiabatic quantum computing (AQC) architectures that are heavily restricted in both connectivity and dynamic range of couplings, for which minor-embedding -- the standard problem mapping method -- cannot be directly applied. Separating the mapping into two distinct stages, we introduce problem-specific reductions for both quadratic unconstrained binary optimisation (QUBO) and satisfiability (SAT) and develop the subdivision-embedding method that is suitable for directly embedding onto these heavily restricted architectures. The theory underpinning this framework provides tools to aid in the manipulation of Ising Hamiltonians for the purposes of Ising energy minimisation, and could be used to assist in developing and optimising further problem mapping techniques. For each of the problem mapping methods presented, we examine how the physical qubit count scales with problem size on architectures of varying connectivity.
A study of smooth contact quasiconformal mappings of the hyperbolic Heisenberg group is presented in this paper. Our main result is a Lifting Theorem; according to this, a symplectic quasiconformal mapping of the hyperbolic plane can be lifted to a circles preserving quasiconformal mapping of the hyperbolic Heisenberg group.