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International Conference on Advanced robotics (ICAR)

作者： Justus Drögemüller Carlos X. Garcia Elena Gambaro Michael Suppa Jochen Steil Máximo A. Roa Technical University of Braunschweig Institute of Robotics and Process Control Technical University of Munich (TUM) Chair of Robotics Artificial Intelligence and Real-time Systems Roboception GmbH German Aerospace Center (DLR)

ISBN: (纸本)9781665436854

This paper proposes a novel approach to automatically generate labeled training data for predicting parallel-jaw grasps from stereo-matched depth images. We generate realistic depth images using Semi-Global Matching to compute disparity maps from synthetic data, which allows producing images that mimic the typical artifacts from real stereo matching in our data, thus reducing the gap from simulation to real execution. Our pipeline automatically generates grasp annotations for single or multiple objects on the synthetically rendered scenes, avoiding any manual image pre-processing steps such as inpainting or denoising. The labeled data is then used to train a CNN-model that predicts parallel-jaw grasps, even in scenarios with large amount of unknown depth values. We further show that scene properties such as the presence of obstacles (a bin, for instance) can be added to our pipeline, and the training process results in grasp prediction success rates of up to 90%.

关键词： Training Annotations Computational modeling Pipelines Noise reduction Training data Manuals

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Stability Analysis and Performance Evaluation of Delayed Bilateral Telerobotic Systems over a Lossy Communication Channel

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Journal of Systems Science & Complexity 2021年第1期34卷 157-179页

作者： BAKHSHI Ali ALFI Alireza TALEBI Heidar Ali SOURATGAR Amir Aboulfazl YOUSEFI Mahdi Faculty of Electrical and Robotic Engineering Shahrood University of TechnologyShahrood 36199-95161Iran Power Plants Control Systems Technology Development Plan Department of monitoring and ControlNiroo Research InstituteTehran 14665-517Iran Real-Time and Robotics system Laboratory Faculty of Electrical EngineeringAmirkabir University of TechnologyHafez AvenueTehran 15914Iran Electrical and Computer Engineering Department The University of British Columbia2385East MallVan couverBC V6T 1Z4Canada

The focus of this paper is to address a novel control technique for stability and transparency analysis of bilateral telerobotic systems in the presence of data loss and time delay in the communication channel. Different control strategies have been reported to compensate the effects of time delay in the communication channel;however, most of them result in poor performance under data loss. First, a model for data loss is proposed using a finite series representation of a set of periodic continuous *** improve the performance and data reconstruction, a holder circuits is also introduced. The passivity of the overall system is provided via the wave variable technique based on the proposed model for the data loss. The stability analysis of the system is then derived using the Lyapunov theorem under the time delay and the data loss. Finally, experimental results are given to illustrate the capability of the proposed control technique.

关键词： Lossy channel passivity stability telerobotic transparency

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Genetic Informed Trees (GIT*): Path planning via reinforced genetic programming heuristics

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Biomimetic Intelligence and robotics 2025年

作者： Liding Zhang Kuanqi Cai Zhenshan Bing Chaoqun Wang Alois Knoll Chair of Robotics Artificial Intelligence and Real-time Systems TUM School of Computation Information and Technology (CIT) Technical University of Munich Munich 85748 Germany Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich Munich 80992 Germany School of Control Science and Engineering Shandong University Jinan 250100 China

Optimal path planning involves finding a feasible state sequence between a start and a goal that optimizes an objective. This process relies on heuristic functions to guide the search direction. While a robust function can improve search efficiency and solution quality, current methods often overlook available environmental data and simplify the function structure due to the complexity of information relationships. This study introduces Genetic Informed Trees (GIT*), which improves upon Effort Informed Trees (EIT*) by integrating a wider array of environmental data, such as repulsive forces from obstacles and the dynamic importance of vertices, to refine heuristic functions for better guidance. Furthermore, we integrated reinforced genetic programming (RGP), which combines genetic programming with reward system feedback to mutate genotype-generative heuristic functions for GIT*. RGP leverages a multitude of data types, thereby improving computational efficiency and solution quality within a set timeframe. Comparative analyses demonstrate that GIT* surpasses existing single-query, sampling-based planners in problems ranging from R 4 to R 16 and was tested on a real-world mobile manipulation task. A video showcasing our experimental results is available at A video showcasing our experimental results is available at https://***/URjXbc_BiYg .

关键词： Genetic algorithm Reinforced genetic programming Generative heuristics Optimal path planning

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Residual Squeeze-and-Excitation Network with Multi-scale Spatial Pyramid Module for Fast Robotic Grasping Detection

Residual Squeeze-and-Excitation Network with Multi-scale Spa...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Hu Cao Guang Chen Zhijun Li Jianjie Lin Alois Knoll Chair of Robotics Artificial Intelligence and Real-Time Systems Technische Universität München München Germany State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Tongji University Shanghai China University of Science and Technology of China China

This paper proposes an efficient, fully convolutional neural network to generate robotic grasps by using 300×300 depth images as input. Specifically, a residual squeeze-and-excitation network (RSEN) is introduced for deep feature extraction. Following the RSEN block, a multi-scale spatial pyramid module (MSSPM) is developed to obtain multi-scale contextual information. The outputs of each RSEN block and MSSPM are combined as inputs for hierarchical feature fusion. Then, the fused global features are upsampled to perform pixel-wise learning for grasping pose estimation. The experimental results on Cornell and Jacquard grasping datasets indicate that the proposed method has a fast inference speed of 5ms while achieving high grasp detection accuracy of 96.4% and 94.8% on Cornell and Jacquard, respectively, which strikes a balance between accuracy and running speed. Our method also gets a 90% physical grasp success rate with a UR5 robot arm.

关键词： Automation Conferences Pose estimation Grasping Manipulators Feature extraction Inference algorithms

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Development of a Cloud- and Edge-Architecture for adaptive model weight optimization of a CNN exemplified by optical detection of hairpin welding

Development of a Cloud- and Edge-Architecture for adaptive m...

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International Electric Drives Production Conference (EDPC)

作者： Johannes Vater Maximilian Kirschning Dominik Scheurenberg Dirk Abel Alois Knoll Planning and Production of Electrified Powertrains BMW Group Munich Germany Chair of Robotics Artificial Intelligence and Real-time Systems Technical University Munich Munich Germany Institute of Automatic Control RWTH Aachen University Aachen Germany

ISBN: (数字)9781728184586

ISBN: (纸本)9781728196145

The beginning of a global reorientation towards an increasingly conscientious approach to nature and the human habitat has been accompanied by changes in industry and society. The automotive industry, where a transition from combustion to electrically powered vehicles is currently underway, is also concerned with this change. In addition to increasing the capacity of the battery, improving the efficiency of the electric motor is essential. To achieve these goals, however, new technologies such as hairpins for the stator are needed. An important process step involves the welding of two pairs of hairpins, which often leads to welding defects. Nevertheless, expert knowledge in this field is limited. Optical monitoring of the welding process with the help of a convolutional neural network (CNN) is a good approach. This approach can compensate for the low level of expert knowledge and detects and classifies welding defects directly in the production line. However, the disadvantage of optical monitoring is that production conditions and the surrounding environment change over time. This has an impact on optical detection and can negatively affect the accuracy of a CNN. For example, the camera perspective can change, which has a negative effect on optical quality monitoring. Therefore, this paper presents an approach for monitoring and evaluating the quality of a CNN in a cloud instance online. If a deteriorating quality is detected, the CNN in the cloud is re-trained by continuously collected data and then automatically deployed to the production line. This allows the CNN to adapt to the changing environmental conditions. The present approach is demonstrated and validated with real data of the stator production process. Compared with the current state-of-the-art, this control loop is highly automated and requires a minimum of human intervention.

关键词： Industries Welding Production Optical computing Stators Monitoring Optimization

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Open Architecture of Single-processor real-time Robot control System Based on Windows NT

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Journal of Donghua University(English Edition) 2003年第4期20卷 123-127页

作者：张广立付莹杨汝清 Research Institute of Robotics Shanghai Jiaotong University Shanghai 200030 China Research Institute of Robotics Shanghai Jiaotong University Shanghai 200030 Chinahis paper introduces the architecture and implementation of an industrial robot control system based on Windows NT. This robot control system which is based on a single-processor structure can run on general industrial computers. Owing to using Windows NT's real-time extension RTX the control system can achieve good realtime performance and friendly user interface in one general-purpose operating system. A three layer hierarchical architecture of control software is proposed to make the system more scalable and flexible. Furthermore a communication and configuration system is implemented to enable modules to communicate with each other which make the control system scalable and flexible.

This paper introduces the architecture and implementation of an industrial robot control system based on Windows NT. This robot control system, which is based on a single-processor structure, can run on general industrial computers. Owing to using Windows NT's real-time extension RTX, the control system can achieve good realtime performance and friendly user interface in one general-purpose operating system. A three layer hierarchical architecture of control software is proposed to make the system more scalable and flexible. Furthermore a communication and configuration system is implemented to enable modules to communicate with each other, which make the control system scalable and flexible.

关键词： robot controller open architecture controller real-time control

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Development of single-chip fuzzy controller based on FFSI in binary

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Journal of Harbin institute of Technology(New Series) 2003年第3期10卷 269-274页

作者：张吉礼欧进萍孙德兴 School of Municipal and Environmental Engineering Harbin Institute of Technology Harbin 150090 China School of the Civil Engineering Harbin Institute of Technology Harbin 150090 China School of Municipal and Environmental Engineering Harbin Institute of Technology Harbin 150090 Chinaength and concise structure of fuzzy logic reasoning program and its real-time reasoning characteristic have their effect on the performance of a digital single-chip fuzzy controller. The control effect of a digital fuzzy controller based on looking up fuzzy control responding table is only relative to the table and not relative to the fuzzy control rules in the practical control process. Aiming at above problem and having combined fuzzy log-ic reasoning with digital operational characteristics of a single-chip microcomputer functioning-fuzzy-subset inference (FFSI) in binary in which triangle membership functions of error and error-in-change are all represented in binary and singleton membership functions of control variable is binary too has been introduced. The circuit principle plans of a single-chip fuzzy controller have been introduced for development of its hardware and the primary program structure fuzzy logic reasoning subroutine serial communication subroutine with PC and reliability design of the fuzzy controller are all discussed in detail. The control of indoor temperature by a fuzzy controller has been conducted using a testing-room thermodynamic system. Research results show that the FFSI in binary can exercise a concise fuzzy control in a single-chip fuzzy controller and the fuzzy controller is therefore reliable and possesses a high performance-price ratio.

Length and concise structure of fuzzy logic reasoning program and its real-time reasoning characteris-tic have their effect on the performance of a digital single-chip fuzzy controller. The control effect of a digitalfuzzy controller based on looking up fuzzy control responding table is only relative to the table and not relative tothe fuzzy control rules in the practical control process. Aiming at above problem and having combined fuzzy log-ic reasoning with digital operational characteristics of a single-chip microcomputer, functioning-fuzzy-subset in-ference (FFSI) in binary, in which triangle membership functions of error and error-in-change are all represen-ted in binary and singleton membership functions of control variable is binary too, has been introduced. The cir-cuit principle plans of a single-chip fuzzy controller have been introduced for development of its hardware, andthe primary program structure, fuzzy logic reasoning subroutine, serial communication subroutine with PC andreliability design of the fuzzy controller are all discussed in detail. The control of indoor temperature by a fuzzycontroller has been conducted using a testing-room thermodynamic system. Research results show that the FFSIin binary can exercise a concise fuzzy control in a single-chip fuzzy controller, and the fuzzy controller is there-fore reliable and possesses a high performance-price ratio.

关键词： functioning-fuzzy-subset inference single-chip fuzzy controller testing-room thermodynamic system indoor temperature experiment

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A system for robot assisted maxillofacial surgery

A system for robot assisted maxillofacial surgery

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6th Conferenc on Medicine Meets Virtual reality, MMVR 1998

作者： Burghart, Catherina R. Muenchenberg, Jan E. Rembold, Ulrich Institute of Real-Time Computer Control Systems and Robotics University of Karlsruhe 76128 Karlsruhe Germany

ISBN: (纸本)9051993862

In maxillofacial surgery the quality of the surgical outcome mainly depends on the experience of the operating surgeon. Thus we intend to support the surgeon before and during surgery in order to enhance the surgical results. On the one hand this implies the use of image processing, three dimensional modelling techniques and visualization techniques of medical image data, on the other hand planning systems, intraoperative navigation devices and surgical robots are needed. In this paper a complex expert system is presented, which uses a planner for generating treatment plans, an infrared navigation for monitoring both patient, robot, and surgical tool, and a surgical robotic system in order to work on bone. Special stress is laid on the architecture of the planning system, the structure of the treatment plans, and the intraopertative communication protocols.

关键词： Robotic surgery

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Knowledgebased segmentation

Knowledgebased segmentation

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6th Conferenc on Medicine Meets Virtual reality, MMVR 1998

作者： Burghart, Catherina R. Pernozzoli, Arno Rembold, Ulrich Institute of Real-Time Computer Control Systems and Robotics University of Karlsruhe 76128 Karlsruhe Germany

ISBN: (纸本)9051993862

The segmentation of medical images like CT or MRI scans represents a great challenge to researchers in computer vision, due to the variability of the individual anatomy and the different characteristics of the scanning systems. As an anatomical knowledge base improves the recognition of structures in CT or MRI scans, we chose a knowledge based segmentation in our approach, which will be explained in the following.

关键词： Computerized tomography

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Range image registration for free-form surfaces using curvature information as invariance 9

Range image registration for free-form surfaces using curvat...

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9th European Signal processing Conference, EUSIPCO 1998

作者： Rieder, Markus Guir, Nicolas Dillmann, R. Department for Computer Science Institute for Real-Time Computer Control Systems and Robotics University of Karlsruhe Karlsruhe76128 Germany Department of Computer Architecture University of Malaga Malaga Spain

A curvature based technique for fast range image registration is described in this work. With this technique the rotation and the displacement of a surface with respect to another one is calculated. The proposed algorithm uses Gaussian curvature information from each image point to extract a number of feature points. Two bounds are applied to the curvature values. Points with these bound curvature value are classified into two classes of feature points. In order to calculate the rotation angle between the two range images, the feature points are paired. That means the angle and the distance of the point pairs have to be transformed into a general view coordinate system. In the orientation matching procedure, we compare each pairing in the first image with each possible in the second one. This process is independent of the translation calculation which is calculated in a sequencing step. This pipelining principle speeds up the registration process if correspondences are calculated constantly.

关键词： Image registration

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