Search Results for author: Frank Kirchner

Found 13 papers, 2 papers with code

Quantum Deep Reinforcement Learning for Robot Navigation Tasks

no code implementations24 Feb 2022 Dirk Heimann, Hans Hohenfeld, Felix Wiebe, Frank Kirchner

In this work, we utilize Quantum Deep Reinforcement Learning as method to learn navigation tasks for a simple, wheeled robot in three simulated environments of increasing complexity.

BIG-bench Machine Learning Quantum Machine Learning +2

The influence of labeling techniques in classifying human manipulation movement of different speed

no code implementations4 Feb 2022 Sadique Adnan Siddiqui, Lisa Gutzeit, Frank Kirchner

In this work, we investigate the influence of labeling methods on the classification of human movements on data recorded using a marker-based motion capture system.

The VVAD-LRS3 Dataset for Visual Voice Activity Detection

no code implementations28 Sep 2021 Adrian Lubitz, Matias Valdenegro-Toro, Frank Kirchner

With a Convolutional Neural Network Long Short Term Memory (CNN LSTM) on facial images an accuracy of 92% was reached on the test set.

Action Detection Activity Detection +1

Black-Box Optimization of Object Detector Scales

no code implementations29 Oct 2020 Mohandass Muthuraja, Octavio Arriaga, Paul Plöger, Frank Kirchner, Matias Valdenegro-Toro

In this work, we propose the use of Black-box optimization methods to tune the prior/default box scales in Faster R-CNN and SSD, using Bayesian Optimization, SMAC, and CMA-ES.

SMAC+

Comparison of Distal Teacher Learning with Numerical and Analytical Methods to Solve Inverse Kinematics for Rigid-Body Mechanisms

1 code implementation29 Feb 2020 Tim von Oehsen, Alexander Fabisch, Shivesh Kumar, Frank Kirchner

We argue that for rigid-body kinematics one of the first proposed machine learning (ML) solutions to inverse kinematics -- distal teaching (DT) -- is actually good enough when combined with differentiable programming libraries and we provide an extensive evaluation and comparison to analytical and numerical solutions.

A Survey of Behavior Learning Applications in Robotics -- State of the Art and Perspectives

no code implementations5 Jun 2019 Alexander Fabisch, Christoph Petzoldt, Marc Otto, Frank Kirchner

Furthermore, we will give an outlook on problems that are challenging today but might be solved by machine learning in the future and argue that classical robotics and other approaches from artificial intelligence should be integrated more with machine learning to form complete, autonomous systems.

BIG-bench Machine Learning

A Framework for On-line Learning of Underwater Vehicles Dynamic Models

no code implementations13 Mar 2019 Bilal Wehbe, Marc Hildebrandt, Frank Kirchner

In this work, a framework for on-line learning of robot dynamics is developed to adapt to such changes.

Incremental Learning regression

Learning of Multi-Context Models for Autonomous Underwater Vehicles

no code implementations17 Sep 2018 Bilal Wehbe, Octavio Arriaga, Mario Michael Krell, Frank Kirchner

Multi-context model learning is crucial for marine robotics where several factors can cause disturbances to the system's dynamics.

General Classification

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