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检索条件"机构=Neuroinformatics and Cognitive Robotics Lab"

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Fast and robust 3D person detector and posture estimator for mobile robotic applications

Fast and robust 3D person detector and posture estimator for...

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2019 International Conference on robotics and Automation, ICRA 2019

作者： Lewandowski, Benjamin Liebner, Jonathan Wengefeld, Tim Muller, Steffen Gross, Horst-Michael Neuroinformatics and Cognitive Robotics Lab Technische Universität Ilmenau Ilmenau98694 Germany

ISBN: (纸本)9781538660263

Due to recent deep learning techniques, person detection seems to be solved in the computer vision domain, however, it is still an issue in mobile robotics. On a robot only limited computing capacities are available. The challenge gets even more difficult when operating in an environment, with people in poses different from the standard upright ones. In this work the environment of a supermarket is considered. Unlike most scenarios targeted by the community, persons not only occur in standing postures, but also grasping into the shelves or squatting in front of them. Furthermore, people are heavily occluded, e.g. by shopping carts. In such a challenging environment, it is important to perceive people early enough and in real-time in order to enable a socially aware navigation. Classical person detectors often suffer from a high posture variance or do not achieve acceptable real-time detection rates. For this reason, different components from the 3D object detection domain have been used to create a new robust person detector for mobile application. Operating on 3D point clouds allows fast detections in real-time up to our goal distance of ten meters and above using the Kinect2 depth sensor. The detector can even differentiate between typical postures of customers who stand or squat in front of shelves. © 2019 IEEE.

关键词： Three-dimensional displays Detectors Feature extraction Robots Histograms Deep learning Task analysis

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Enhancing Person Perception for Mobile robotics by Real-Time RGB-D Person Attribute Estimation

Enhancing Person Perception for Mobile Robotics by Real-Time...

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2024 IEEE/SICE International Symposium on System Integration, SII 2024

作者： Wengefeld, Tim Seichter, Daniel Lewandowski, Benjamin Gross, Horst-Michael Technische Universität Ilmenau Neuroinformatics and Cognitive Robotics Lab Ilmenau98694 Germany

ISBN: (纸本)9798350312072

Person attribute estimation is a task of great importance for a variety of real-world robotic applications. While the computer vision community has made impressive progress over the last decade, they often rely on the sole use of RGB images from surveillance datasets and large deep- learning models without considering real-time requirements. By contrast, mobile robotic platforms have to deal with restricted resources but are often equipped with RGB-D cameras, offering complementary modalities. This paper presents an approach to robustly estimate soft-biometric attributes from full-body RGB-D appearances of persons in the surroundings of a mobile robot. The effects of depth, RGB and RGB-D data as input are analyzed, taking into account runtime and resource requirements. On the robotic attribute dataset SRL, it is shown that the presented approach outperforms other state-of-the-art approaches by a large margin. Furthermore, real-time requirements are met when applied on an NVIDIA Jetson AGX Xavier or even on a mobile CPU only. Finally, a previous system for person detection, upper body orientation estimation, and posture classification is integrated to enable an even more comprehensive perception of persons in the surroundings of a mobile robot in one joint approach. The source code for training and application will be made publicly available on GitHub. © 2024 IEEE.

关键词： Mobile robots

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Playing hide and seek with a mobile companion robot

Playing hide and seek with a mobile companion robot

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2011 11th IEEE-RAS International Conference on Humanoid Robots, HUMANOIDS 2011

作者： Volkhardt, Michael Mueller, Steffen Schroeter, Christof Gross, Horst-Michael Neuroinformatics and Cognitive Robotics Lab. Ilmenau University of Technology 98684 Ilmenau Germany

ISBN: (纸本)9781612848679

This paper addresses the problem of finding people in domestic environments utilizing a mobile robot. Companion robots, which should provide different services, must be able to robustly estimate the user's position. While detecting people in an upright pose is mainly solved, most of the users' various poses in living environments are hard to detect. We present a tracking framework that incorporates state-of-the-art detection modules, but also a novel approach for visually detecting the presence of people resting at previously known seating places in arbitrary poses. The method is based on a contextual color model of the respective place in the environment and a color model of the user's appearance. The system has been tested by evaluating the robot's capability to find the user in a 3-room apartment in a hide and seek scenario. © 2011 IEEE.

关键词： Color

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How to always keep an eye on the user with a mobile robot?* 50

How to always keep an eye on the user with a mobile robot?*

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50th International Symposium on robotics, ISR 2018

作者： Vorndran, Alexander Trinh, Thanh Q. Müller, Steffen Scheidig, Andrea Groß, Horst-Michael Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology POB 100565 Ilmenau98684 Germany

ISBN: (纸本)9781510870314

Using mobile robots in rehabilitation is an upcoming trend in the field of robotic healthcare. A possible application is robot assisted self-training after orthopedic knee or hip endoprosthesis surgery. In this scenario, it is particularly important to be able to continuously observe the patients movements in order to give timely feedback on the ongoing exercise. This paper presents a complementary approach separately taking care of two fundamental prerequisites of an application scenario where a user performs gait retraining in rehabilitation under supervision of a mobile robot: driving at a certain constant distance in front of the user and keeping the user at a suitable position in the sensor’s field of view. We show the applicability of our approach under laboratory and real-world conditions. © VDE VERLAG GMBH · Berlin · Offenbach

关键词： Mobile robots

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"Take a seat, please": Approaching and recognition of seated persons by a mobile robot 50

"Take a seat, please": Approaching and recognition of seated...

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50th International Symposium on robotics, ISR 2018

作者： Trinh, Thanh Q. Wengefeld, Tim Müller, Steffen Vorndran, Alexander Volkhardt, Michael Scheidig, Andrea Gross, Horst-Michael Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology PF 100565 Ilmenau98684 Germany

ISBN: (纸本)9781510870314

As a long-term goal, robots should be able to interact with humans in multiple forms in order to assist them in everyday life. Over the course of several projects with public operational environments, for our mobile robots equipped with touch displays as primary input/output device, we found an intuitive way to interact with the robot is in a seated position and being approached by the robot, so that the user can physically operate the robot. Sitting down is also a signal for interaction intention which is easily conveyed and even visible from afar, as opposed to speech recognition systems. To realize this behavior, we propose a succinct yet effective method of recognizing a seated person by utilizing the height estimation of a person detector, as well as a method of finding an interaction pose to approach the user and navigating to that pose even in dynamic unstructured environments. The proposed approaches are evaluated in an experimental setup similar to the dynamic hospital environment of our project ROGER where a robotic gait training coach for orthopedic rehabilitation of patient with hip prosthesis is developed. © VDE VERLAG GMBH · Berlin · Offenbach

关键词： Mobile robots

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May i be your personal coach? Bringing together person tracking and visual re-identification on a mobile robot 47

May i be your personal coach? Bringing together person track...

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47th International Symposium on robotics, ISR 2016

作者： Wengefeld, Tim Eisenbach, Markus Trinh, Thanh Q. Gross, Horst-Michael Ilmenau University of Technology Neuroinformatics and Cognitive Robotics Lab PF 100565 Ilmenau98684 Germany

ISBN: (纸本)9783800742318

Mobile robots following and guiding stroke patients during their rehabilitation program are in the focus of our research in rehabilitation robotics. To be able to act autonomously, it is crucial for the robot to extract long and precise movement trajectories of the patients. But already keeping track on one specific person in a crowded dynamic environment is inherently hard, since multi-sensor tracking as well as appearance-based re-identification are challenging tasks in realworld environments. Therefore, we aim for developing a coupled person tracking system that combines user tracking by spatial proximity with appearance-based user recognition. We analyzed all subcomponents of such a system and identified four essential parts, that significantly influence the overall performance. We show, that it is essential, to (1) accurately detect all persons in scene, (2) track people as long as no ambiguities occur, (3) visually re-identify the user otherwise, and (4) reduce the search space for re-identification to just relevant hypotheses using spatial proximity as criterion. In our experiments, we show, that by addressing all these aspects, our system significantly outperforms each approach, that excludes just one of these important parts. © 2016 VDE VERLAG GMBH Berlin Offenbach.

关键词： Mobile robots

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Situation Awareness for Autonomous Agents 27

Situation Awareness for Autonomous Agents

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27th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2018

作者： Dahnl, Nikolas Grass, Horst-Michael Fuchs, Stefan Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology Ilmenau98693 Germany Honda Research Institute Offenbach63073 Germany

ISBN: (纸本)9781538679807

Situation Awareness is a prominent concept in the human factors community. It is used to analyze and eliminate common sources of human errors in complex tasks and has seen wide-spread use in many fields, such as aviation, health care or ergonomics. Humans who are situation aware are able to reliably generate competent performance, a skill that is also highly desired for other autonomous agents. Yet, the concept has seen only limited use in robotics. We attest this to a lack of clear definitions which would allow assessing an artificial agents capacity for Situation Awareness. Our major contribution is an application-agnostic definition of the terminology and the processes involved in acquiring Situation Awareness. By integrating our definitions into the perception-action-cycle we provide a connection to the agent's observable behavior. Our second major contribution is a way to estimate, whether an agent has lost Situation Awareness based on surprise. This measure can be used online and does not require explicit or implicit knowledge of the task. We evaluate our concept on a physical workspace built for abstract Human- Robot-Cooperation scenarios. © 2018 IEEE.

关键词： Autonomous agents

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Automated classification of therapeutic face exercises using the kinect

Automated classification of therapeutic face exercises using...

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8th International Conference on Computer Vision Theory and Applications, VISAPP 2013

作者： Lanz, Cornelia Olgay, Birant Sibel Denzler, Joachim Gross, Horst-Michael Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology Ilmenau Germany Computer Vision Group Friedrich Schiller University Jena Jena Germany

ISBN: (纸本)9789898565471

In this work, we propose an approach for the unexplored topic of therapeutic facial exercise recognition using depth images. In cooperation with speech therapists, we determined nine exercises that are beneficial for therapy of patients suffering from dysfunction of facial movements. Our approach employs 2.5D images and 3D point clouds, which were recorded using Microsoft's Kinect. Extracted features comprise the curvature of the face surface and characteristic profiles that are derived using distinctive landmarks. We evaluate the discriminative power and the robustness of the features with respect to the above-mentioned application scenario. Using manually located face regions for feature extraction, we achieve an average recognition accuracy of about 91% for the nine facial exercises. However in a real-world scenario manual localization of regions for feature extraction is not feasible. Therefore, we additionally examine the robustness of the features and show, that they are beneficial for a real-world, fully automated scenario as well.

关键词： Feature extraction

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Ensembles of neural networks for robust reinforcement learning

Ensembles of neural networks for robust reinforcement learni...

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9th International Conference on Machine Learning and Applications, ICMLA 2010

作者： Hans, Alexander Udluft, Steffen Neuroinformatics and Cognitive Robotics Lab. Ilmenau University of Technology Ilmenau Germany Intelligent Systems and Control Siemens AG Corporate Technology Munich Germany

ISBN: (纸本)9780769543000

Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their training and the validation of final policies can be cumbersome as neural networks can suffer from problems like local minima or overfitting. When using iterative methods, such as neural fitted Q-iteration, the problem becomes even more pronounced since the network has to be trained multiple times and the training process in one iteration builds on the network trained in the previous iteration. Therefore errors can accumulate. In this paper we propose to use ensembles of networks to make the learning process more robust and produce near-optimal policies more reliably. We name various ways of combining single networks to an ensemble that results in a final ensemble policy and show the potential of the approach using a benchmark application. Our experiments indicate that majority voting is superior to Q-averaging and using heterogeneous ensembles (different network topologies) is advisable. © 2010 IEEE.

关键词： Iterative methods

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Generating motion trajectories by sparse activation of learned motion primitives

Generating motion trajectories by sparse activation of learn...

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22nd International Conference on Artificial Neural Networks, ICANN 2012

作者： Vollmer, Christian Eggert, Julian P. Gross, Horst-Michael Ilmenau University of Technology Neuroinformatics and Cognitive Robotics Lab. Ilmenau 98684 Germany Honda Research Institute Europe GmbH Offenbach/Main 63073 Germany

ISBN: (纸本)9783642332685

We interpret biological motion trajectories as composed of sequences of sub-blocks or motion primitives. Such primitives, together with the information, when they occur during a motion, provide a compact representation of movement. We present a two-layer model for movement generation, where the higher level consists of a number of spiking neurons that trigger motion primitives in the lower level. Given a set of handwritten character trajectories, we learn motion primitives, together with the timing information, with a variant of shift-NMF that is able to cope with large data sets. From the timing information for a class of characters, we then learn a generative model based on a stochastic Integrate-and-Fire neuron model. We show that we can generate good reconstructions of characters with shared primitives for all characters modeled. © 2012 Springer-Verlag.

关键词： Trajectories

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