Direct solutions to tropical optimization problems with nonlinear objective functions and boundary constraints

We examine two multidimensional optimization problems that are formulated in terms of tropical mathematics. The problems are to minimize nonlinear objective functions, which are defined through the multiplicative conjugate vector transposition on vectors of a finite-dimensional semimodule over an idempotent semifield, and subject to boundary constraints. The solution approach is implemented, which involves the derivation of the sharp bounds on the objective functions, followed by determination of vectors that yield the bound. Based on the approach, direct solutions to the problems are obtained in a compact vector form. To illustrate, we apply the results to solving constrained Chebyshev approximation and location problems, and give numerical examples.Comment: Mathematical Methods and Optimization Techniques in Engineering: Proc. 1st Intern. Conf. on Optimization Techniques in Engineering (OTENG '13), Antalya, Turkey, October 8-10, 2013, WSEAS Press, 2013, pp. 86-91. ISBN 978-960-474-339-

Fast Simulation of Vehicles with Non-deformable Tracks

This paper presents a novel technique that allows for both computationally fast and sufficiently plausible simulation of vehicles with non-deformable tracks. The method is based on an effect we have called Contact Surface Motion. A comparison with several other methods for simulation of tracked vehicle dynamics is presented with the aim to evaluate methods that are available off-the-shelf or with minimum effort in general-purpose robotics simulators. The proposed method is implemented as a plugin for the open-source physics-based simulator Gazebo using the Open Dynamics Engine.Comment: Submitted to IROS 201

Combination of t-norms and their conorms

summary:Non-negative linear combinations of $t_{\min}$-norms and their conorms are used to formulate some decision making problems using systems of max-separable equations and inequalities and optimization problems under constraints described by such systems. The systems have the left hand sides equal to the maximum of increasing functions of one variable and on the right hand sides are constants. Properties of the systems are studied as well as optimization problems with constraints given by the systems and appropriate solution methods are proposed. Motivation of this research are decision making investment situations both in deterministic and uncertain environment. Possibilities of further research are briefly discussed in the concluding remarks of the paper

An approach to the solution of a conflict situation with nn participants

summary:In this article an attempt is made to find in a certain sense reasonable probabilistic preference group order. The criterion of reasonability of the group preference order is the value of a real function (the so called function of discontent) defined on a set of feasible group decision rules, each of which determines a probabilistic preference ordering on a given set of alternatives. The decision rules minimizing the value of the function $f$ over the set of feasible group decisoin rules are supposed to be reasonable for the whole group and can be recommended to the leader of the group as a "reasonable dictate". The members of the group, who tend to minimize the value of the function $f$, if appointed leaders of the whole group, are called reasonable dictators (the set \Cal D_r(f) in the text). The problem of choosing in a sense the "most suitable reasonable dictators" is considered (the set \Cal D_r(f, \phi) in the text). The solution of a given conflict situation is then a pair $(P;j)$, where $P$ is a reasonable group decision rule ("reasonable dictate" for the whole group) and $j$ is a suitable reasonable dictator, i.e. a person from the group, who can apply this reasonable dictate if appointed the leader of the group. Existence conditions for the solution of the conflict situation are given and various possibilities of extension of the proposed models are considered. A small numerical example is solved

Self-Supervised Depth Correction of Lidar Measurements from Map Consistency Loss

Depth perception is considered an invaluable source of information in the context of 3D mapping and various robotics applications. However, point cloud maps acquired using consumer-level light detection and ranging sensors (lidars) still suffer from bias related to local surface properties such as measuring beam-to-surface incidence angle, distance, texture, reflectance, or illumination conditions. This fact has recently motivated researchers to exploit traditional filters, as well as the deep learning paradigm, in order to suppress the aforementioned depth sensors error while preserving geometric and map consistency details. Despite the effort, depth correction of lidar measurements is still an open challenge mainly due to the lack of clean 3D data that could be used as ground truth. In this paper, we introduce two novel point cloud map consistency losses, which facilitate self-supervised learning on real data of lidar depth correction models. Specifically, the models exploit multiple point cloud measurements of the same scene from different view-points in order to learn to reduce the bias based on the constructed map consistency signal. Complementary to the removal of the bias from the measurements, we demonstrate that the depth correction models help to reduce localization drift. Additionally, we release a data set that contains point cloud data captured in an indoor corridor environment with precise localization and ground truth mapping information.Comment: Accepted to RA-L 2023: https://www.ieee-ras.org/publications/ra-

Johannes Trüper: Ein Heilpädagoge zwischen Pädagogik und Kinder- und Jugendpsychiatrie

Johannes Trüper (1855-1921) gründete 1890 in Jena das heilpädagogische Institut "Sophienhöhe", welches sich im Laufe der nächsten dreißig Jahre zu einer weltbekannten Einrichtung entwickeln sollte. Er beschritt in der Zusammenarbeit mit den führenden Wissenschaftlern auf dem Gebiet der Psychiatrie und Pädagogik seiner Zeit neue Wege und erreichte einen hohen Grad an Professionalität. Die Arbeit beleuchtet seinen persönlichen Werdegang und die Entwicklung der Einrichtung. Gleichzeitig bemüht sich die Arbeit, den ideengeschichtlichen, wirtschaftlichen und politischen Hintergrund dieser Entwicklung zu analysieren und gewinnt damit Erklärungen für Johannes Trüpers Verschwinden in der wissenschaftlichen Bedeutungslosigkeit

Data-driven Policy Transfer with Imprecise Perception Simulation

The paper presents a complete pipeline for learning continuous motion control policies for a mobile robot when only a non-differentiable physics simulator of robot-terrain interactions is available. The multi-modal state estimation of the robot is also complex and difficult to simulate, so we simultaneously learn a generative model which refines simulator outputs. We propose a coarse-to-fine learning paradigm, where the coarse motion planning is alternated with imitation learning and policy transfer to the real robot. The policy is jointly optimized with the generative model. We evaluate the method on a real-world platform in a batch of experiments.Comment: Submitted to IROS 2018 with RAL optio

MonoForce: Self-supervised learning of physics-aware grey-box model for predicting the robot-terrain interaction

We introduce an explainable, physics-aware, and end-to-end differentiable model which predicts the outcome of robot-terrain interaction from camera images. The proposed MonoForce model consists of a black-box module, which predicts robot-terrain interaction forces from the onboard camera, followed by a white-box module, which transforms these forces through the laws of classical mechanics into the predicted trajectories. As the white-box model is implemented as a differentiable ODE solver, it enables measuring the physical consistency between predicted forces and ground-truth trajectories of the robot. Consequently, it creates a self-supervised loss similar to MonoDepth. To facilitate the reproducibility of the paper, we provide the source code. See the project github for codes and supplementary materials such as videos and data sequences

Transverse Instabilities of the LHC Proton Beam in the SPS

The availability from the injectors of the proton beam required for the LHC era has allowed studying its transverse behaviour in the SPS. Profile and beam oscillation measurements evidenced the existence of strong transverse instabilities developing along the batch and inducing an emittance blow-up of increasing importance from the head to the tail of the batch. An intensity threshold, comparable to that observed for the development of the beam induced electron cloud, has been found for the onset of the above phenomena. The results of the measurements and their possible interpretation are presented