Search our Publications

Results

Xilu Wang, Yaochu Jin, Sebastian Schmitt, Markus Olhofer, "Transfer Learning Based Co-surrogate Assisted Evolutionary Bi-objective Optimization for Objectives with Non-uniform Evaluation Times", Evolutionary Computation journal (ECJ), 2021.

Abstract

Most existing multiobjetive evolutionary algorithms (MOEAs) implicitly assume that each objective function can be evaluated within the same period of time, which is un- tenable in many real-world optimization scenarios where evaluation of different ob- jectives involves different computer simulations or physical experiments with distinct time complexity. To address this issue, a transfer learning scheme based on surrogate- assisted evolution...



Download Bibtex file Download PDF

Charlie Street, Sebastian Pütz, Manuel Mühlig, Nick Hawes, Bruno Lacerda, "Congestion-Aware Policy Synthesis for Multirobot Systems", IEEE Transactions on Robotics, pp. 1-19, 2021.

Abstract

Multi-robot systems must be able to maintain performance when robots get delayed during execution. For mobile robots, one source of delays is congestion. Congestion occurs when robots deployed in shared physical spaces interact, as robots present in the same area simultaneously must manoeuvre to avoid each other. Congestion can adversely affect navigation performance, and increase the duration of navigation actions. In this paper, we prese...



Download Bibtex file Download PDF

Guo Yu, Yaochu Jin, Markus Olhofer, Qiqi Liu, Wenli Du, "Solution Set Augmentation for Knee Identification in Multiobjective Decision Analysis", IEEE Transactions on Cybernetics, pp. 1-14, 2021.

Abstract

In multiobjective decision making, most knee identification algorithms implicitly assume that the given solutions are well distributed and can provide sufficient information for identifying knee solutions. However, this assumption may fail to hold when the number of objectives is large or when the shape of the Pareto front is complex. To address the above issues, we propose a knee-oriented solution augmentation (KSA) framework that converts the P...



Download Bibtex file Download PDF

Alicia Schildhauer, "Human-robot cooperation for solving a manipulation task in the context of outpatient elderly care ", Berliner Hochschule für Technik, 2021.

Abstract

Technology for elderly care is becoming increasingly important due to the rising number of people turning old and at the same time the number of care workers decreasing. This bachelor’s thesis gives an introductory investigation on a future in elderly-robot cooperation. A focus is set on the selection and evaluation of different possible interaction tasks. Also, the relevance of various interaction modes is taken into account, to discover, ...



Download Bibtex file Per Mail Request

Sneha Saha, "3D Variational Point Cloud Autoencoders as Generative Models for Design Optimization", BWM office visit, 2021.

Abstract

This is a technical presentation about our previous research in the ECOLE project. The presentation includes our research motivation, with the introduction to variational autoencoder models and the application of this model for design optimization tasks. The research for the presentations is from previously published papers....



Download Bibtex file Per Mail Request

Yasuyuki Shimizu, "Structural Behavior Clustering Methods for Topologically-Optimized Designs", Technische Universität München, 2021.

Abstract

This thesis shows how to distinguish the dynamic structural behavior under the crash loading using several distance metrics to compare each time series data and clustering algorithms. Dynamic Time Warping is used to compare time series, which have different time scales. For the clustering method, OPTICS and k-medoids methods are used and compared. The first part deals with some simple examples, such as the movement of a spring system and beam...



Download Bibtex file Per Mail Request

Tuan Pham, "User Experience in Interactive Object Learning: Pleasurable Teaching Practices with Learning Robots", University of Siegen, 2021.

Abstract

While the training of learning robot systems has been implemented for various purposes and with desirable results, little emphasis has been put on motivational and experiential aspects of the human teacher. Without establishing pleasurable and engaging teaching practices, the training of an intelligent agent remains a tedious task that humans may only perform voluntarily for short periods. The main goal of this thesis is therefore to expl...



Download Bibtex file Per Mail Request

Thiago Rios, Bas van Stein, Patricia Wollstadt, Thomas Bäck, Bernhard Sendhoff, Stefan Menzel, "Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders", IEEE Congress on Evolutionary Computation 2021, 2021.

Abstract

Methods for learning and compressing high-dimensional data allow designers to generate novel and low-dimensional design representations for shape optimization problems. By using compact design spaces, global optimization algorithms require less function evaluations to characterize the problem landscape. Furthermore, data-driven representations are often domain-agnostic and independent of the user expertise, and thus potentially capture more relev...



Download Bibtex file Download PDF

Sneha Saha, Leandro Minku, Xin Yao, Bernhard Sendhoff, Stefan Menzel, "Exploiting Linear Interpolation of Variational Autoencoders for Satisfying Preferences in Evolutionary Design Optimization", IEEE Congress on Evolutionary Computation (CEC), 2021.

Abstract

In the early design phase of automotive digital development, one of the key challenges for the designer is to consider multiple-criteria like aerodynamics and structural efficiency besides aesthetic aspects for designing a car shape. In our research, we imagine a cooperative design system in the automotive domain which provides guidance to the designer for finding sets of design options or well-performing designs for preferred search areas. In th...



Download Bibtex file Download PDF

Hung Lin, "Cost-oriented Topology Optimization with Manufacturing Constraints", Technische Universität München, 2021.

Abstract

This thesis proposes a framework of gradient-based topology optimization (TO), which is able to handlenon-continuous objective functions (e.g. total cost) with multiple constraints, via using the finite difference (FD) scheme for the sensitivities. The thesis especially focuses on the sheet metal stamping process in the automotive industry, thus the cost of such process is set as the objective, submitted to given maximum compliance as constraint....



Download Bibtex file Per Mail Request

1 ... 3 4 5 6 7 8 ... 130

Search