检索结果-内蒙古大学图书馆

Unifying Skill-Based programming and programming by demonstration through Ontologies

Procedia Computer Science 2024年 232卷 595-605页

作者： Thomas Eiband Florian Lay Korbinian Nottensteiner Dongheui Lee Institute of Robotics and Mechatronics German Aerospace Center (DLR) Münchener Str. 20 82234 Wessling Germany Autonomous Systems Technische Universität Wien (TU Wien) Gußhausstraße 27-29/384 1040 Vienna Austria

Smart manufacturing requires easily reconfigurable robotic systems to increase the flexibility in presence of market uncertainties by reducing the set-up times for new tasks. One enabler of fast reconfigurability is given by intuitive robot programming methods. On the one hand, offline skill-based programming (OSP) allows the definition of new tasks by sequencing pre-defined, parameterizable building blocks termed as skills in a graphical user interface. On the other hand, programming by demonstration (PbD) is a well known technique that uses kinesthetic teaching for intuitive robot programming, where this work presents an approach to automatically recognize skills from the human demonstration and parameterize them using the recorded data. The approach further unifies both programming modes of OSP and PbD with the help of an ontological knowledge base and empowers the end user to choose the preferred mode for each phase of the task. In the experiments, we evaluate two scenarios with different sequences of programming modes being selected by the user to define a task. In each scenario, skills are recognized by a data-driven classifier and automatically parameterized from the recorded data. The fully defined tasks consist of both manually added and automatically recognized skills and are executed in the context of a realistic industrial assembly environment.

关键词： intuitive programming smart factory skill recognition robot skills programming by demonstration Learning from demonstration user interface kinesthetic teaching ontology knowledge base

来源：评论

学校读者我要写书评

暂无评论

Motion capture and AR based programming by demonstration for industrial robots using handheld teaching device

引用

SCIENTIFIC REPORTS 2024年第1期14卷 1-24页

作者： Liu, Guoliang Sun, Wenlei Li, Pinwen Xinjiang Univ Sch Mech Engn Urumqi 830017 Peoples R China

In the industrial robots field, efficient and convenient programming methods have been a hot research topic. In recent years, immersive simulation technology has been developing rapidly in many fields, which provides new horizons for the development of industrial robots. This paper presents a HTC VIVE laser scan motion capture and Holohens augmented reality (AR) based interactive programming by demonstration (PbD) system for industrial robot. A portable Handheld Teaching Device (HTD) and its calibration algorithm are designed in the system. The portable HTD which is tracked by a laser motion capture system can be viewed as an AR robot end-effector to teach paths. Meanwhile, the AR robot can be simulated in real time during programing. In addition, the robot reproducing the operator's actions at the same position in space is the focus of programming. So, Multi-system registration methods are proposed to determine the relationship between robot systems, motion capture systems and virtual robot systems. Meanwhile, a path planning algorithm is proposed to convert the captured raw path points into robot-executable code. For unskilled operators, they can easily perform complex programming using the HTD. For skilled senior workers, their skills can be quickly learned by robots using the system.

关键词： Robots Motion capture AR programming by demonstration

来源：评论

学校读者我要写书评

暂无评论

Knowledge Based Accuracy Improvement in programming by demonstration of Point Based Processes 30th

Knowledge Based Accuracy Improvement in Programming by Demon...

引用

30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM)

作者： Ikeda, Markus Chitturi, Naresh Ganglbauer, Markus Pichler, Andreas PROFACTOR GmbH Stadtgut D1 AT-4407 Steyr Gleink Austria

Productivity and flexibility are antagonists with opposite goals. Until now, optimal productivity could only be achieved in fully automated inflexible serial production. Increased demand for flexibility due to individualized products e.g. in most SMEs requires an increased level of flexibility - also for robots that should provide improved skills as well as improved means of interaction to simplify programming. Instrumented tools based on 3D tracking technology can be used as interfaces in programming by demonstration (PbD) scenarios but are prone to inaccuracies introduced by human demonstration. This paper presents a programming paradigm that combines a semantic model based geometric reasoning paradigms with an instrumented tool based PbD approach in order to compensate those introduced inaccuracies as well as investigates basic accuracies of demonstration of point based operations. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： knowledge based robotics virtual reality mixed reality programming by demonstration human robot interaction

来源：评论

学校读者我要写书评

暂无评论

An inertial human upper limb motion tracking method for robot programming by demonstration

引用

ROBOTICS AND AUTONOMOUS SYSTEMS 2022年 156卷

作者： Pellois, Robin Bruls, Olivier Univ Liege Dept Aerosp & Mech Engn Liege Belgium

This paper proposes an inertial human motion tracking for robot programming by demonstration (PbD). An original element called heading reset is proposed to catch the drift around gravity direction. It is based on a hypothesis made on the human arm motion during a task demonstration. It is used to overcome the non-use of the magnetometer due to magnetic disturbances from robotic environment. This element is implemented in an orientation estimation algorithm and compared with three other IMU algorithms and a commercial MARG algorithm. The human arm trajectory is estimated through three IMUs sensors directly set on the arm to estimate the segment orientation (hand, forearm and arm). A specific inertial-2-segment procedure is presented as well as a procedure to estimate the transformation from human reference frame to task frame, necessary for a PbD process. Experimental tests, using a robot as a reference, have been conducted to validate the different part of the method. The heading reset and the orientation algorithm show good results. The inertial-2-segment procedure is shown to be robust. Finally, experimental tests on a human arm and physical robot validate the complete method. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Robotics programming by demonstration Inertial human motion tracking

来源：评论

学校读者我要写书评

暂无评论

Joining Force of Human Muscular Task Planning With Robot Robust and Delicate Manipulation for programming by demonstration

引用

IEEE-ASME TRANSACTIONS ON MECHATRONICS 2020年第5期25卷 2574-2584页

作者： Wang, Fei Zhou, Xingqun Wang, Jianhui Zhang, Xing He, Zhenquan Song, Bo Northeastern Univ Fac Robot Sci & Engn Shenyang 110169 Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Chinese Acad Sci Inst Intelligent Machines Hefei 230031 Peoples R China

Recently, programing by demonstration (PbD) received much attention for its capacity of fast programming with increasing demands in the robot manipulation area, especially in industrial applications. However, one of the biggest challenges of PbD is the recognition of demonstrator's finger high-fidelity motions especially in the environments with uncertainties, which limits the efficiency and accuracy of PbD. In this article, inspired by human dexterity, a novel PbD approach using the implicit muscular task planning strategy is presented to extract features from the arms' giant movement and the hands' fine motions during the demonstrator's operation. Furthermore, we integrate a deep reinforcement learning control method that further improves the manipulations' adaptive ability in the unknown or dynamic environments. The experimental results show that our proposed approach can deal with relative complex assembly tasks with a success rate of more than 67% within a fit tolerance of 4.2 mm by one-shot demonstration.

关键词： Task analysis Robot sensing systems Gesture recognition IEEE transactions Mechatronics Robotic assembly Implicit muscular task planning multisource information fusion programming by demonstration reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

programming by demonstration Using the Teleimpedance Control Scheme: Verification by an sEMG-Controlled Ball-Trapping Robot

引用

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2019年第2期15卷 998-1006页

作者： Park, Seongsik Lee, Woongyong Chung, Wan Kyun Kim, Keehoon Korea Inst Sci & Technol Interact & Robot Res Ctr Seoul 02792 South Korea Pohang Univ Sci & Technol Dept Mech Engn Pohang 37673 South Korea

Impedance control allows robots to manipulate physical interactions delicately. However, issues associated with path planning and impedance remain unresolved. Herein we propose a path and impedance planning method for impedance control in a robot based on programming by demonstration through telemanipulation using a surface electromyogram. We considered a task that requires quick and precise adjustment of path and impedance, that is, ball trapping. We implemented a teleoperated robot that can deliver an operator's impedance as well as position during the ball trapping task to the slave side. The operators were asked to perform demonstrations of ball-trapping tasks using the implemented teleoperated robot, where the slave side is a vertical robot with one degree of freedom. The path and impedance were recorded and programmed as control input profiles from a set of successful demonstrations using Gaussian mixture regression. The result showed that using the human demonstration, the robot could learn how to catch a dropped ball without rebounding.

关键词： Impedance control programming by demonstration surface electromyogram teleimpedance control

来源：评论

学校读者我要写书评

暂无评论

A spatial information inference method for programming by demonstration of assembly tasks by integrating visual observation with CAD model

引用

ASSEMBLY AUTOMATION 2020年第5期40卷 689-701页

作者： Zhou, Zhongxiang Ji, Liang Xiong, Rong Wang, Yue Zhejiang Univ State Key Lab Ind Control Technol Hangzhou Peoples R China

Purpose In robot programming by demonstration (PbD) of small parts assembly tasks, the accuracy of parts poses estimated by vision-based techniques in demonstration stage is far from enough to ensure a successful execution. This paper aims to develop an inference method to improve the accuracy of poses and assembly relations between parts by integrating visual observation with computer-aided design (CAD) model. Design/methodology/approach In this paper, the authors propose a spatial information inference method called probabilistic assembly graph with optional CAD model, shorted as PAGC*, to achieve this task. Then an assembly relation extraction method from CAD model is designed, where different assembly relation descriptions in CAD model are summarized into two fundamental relations that are colinear and coplanar. The relation similarity, distance similarity and rotation similarity are adopted as the similar part matching criterions between the CAD model and the observation. The knowledge of part in CAD is used to correct that of the corresponding part in observation. The likelihood maximization estimation is used to infer the accurate poses and assembly relations based on the probabilistic assembly graph. Findings In the experiments, both simulated data and real-world data are applied to evaluate the performance of the PAGC* model. The experimental results show the superiority of PAGC* in accuracy compared with assembly graph (AG) and probabilistic assembly graph without CAD model (PAG). Originality/value The paper provides a new approach to get the accurate pose of each part in demonstration stage of the robot PbD system. By integrating information from visual observation with prior knowledge from CAD model, PAGC* ensures the success in execution stage of the PbD system.

关键词： Assembly tasks CAD model programming by demonstration Spatial information inference

来源：评论

学校读者我要写书评

暂无评论

Knowledge Based Accuracy Improvement in programming by demonstration of Point Based Processes

引用

Procedia Manufacturing 2021年 55卷 16-23页

作者： Markus Ikeda Naresh Chitturi Markus Ganglbauer Andreas Pichler PROFACTOR GmbH Im Stadtgut D1 AT-4407 Steyr-Gleink Austria

Productivity and flexibility are antagonists with opposite goals. Until now, optimal productivity could only be achieved in fully automated inflexible serial production. Increased demand for flexibility due to individualized products e.g. in most SMEs requires an increased level of flexibility – also for robots that should provide improved skills as well as improved means of interaction to simplify programming. Instrumented tools based on 3D tracking technology can be used as interfaces in programming by demonstration (PbD) scenarios but are prone to inaccuracies introduced by human demonstration. This paper presents a programming paradigm that combines a semantic model based geometric reasoning paradigms with an instrumented tool based PbD approach in order to compensate those introduced inaccuracies as well as investigates basic accuracies of demonstration of point based operations.

关键词： knowledge based robotics virtual reality mixed reality programming by demonstration human robot interaction

来源：评论

学校读者我要写书评

暂无评论

Combining programming by demonstration with Path Optimization and Local Replanning to Facilitate the Execution of Assembly Tasks

Combining Programming by Demonstration with Path Optimizatio...

引用

IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Gorjup, Gal Kontoudis, George P. Dwivedi, Anany Gao, Geng Matsunaga, Saori Mariyama, Toshisada MacDonald, Bruce Liarokapis, Minas Univ Auckland Dept Mech Engn Auckland New Zealand Virginia Tech Bradley Dept Elect & Comp Engn Blacksburg VA USA Mitsubishi Electr Corp Informat Technol R&D Ctr Tokyo Japan Univ Auckland Ctr Automat & Robot Engn Sci Auckland New Zealand

ISBN: (纸本)9781728185262

With the emergence of agile manufacturing in highly automated industrial environments, the demand for efficient robot adaptation to dynamic task requirements is increasing. For assembly tasks in particular, classic robot programming methods tend to be rather time intensive. Thus, effectively responding to rapid production changes requires faster and more intuitive robot teaching approaches. This work focuses on combining programming by demonstration with path optimization and local replanning methods to allow for fast and intuitive programming of assembly tasks that requires minimal user expertise. Two demonstration approaches have been developed and integrated in the framework, one that relies on human to robot motion mapping (teleoperation based approach) and a kinesthetic teaching method. The two approaches have been compared with the classic, pendant based teaching. The framework optimizes the demonstrated robot trajectories with respect to the detected obstacle space and the provided task specifications and goals. The framework has also been designed to employ a local replanning scheme that adjusts the optimized robot path based on online feedback from the camera-based perception system, ensuring collision-free navigation and the execution of critical assembly motions. The efficiency of the methods has been validated through a series of experiments involving the execution of assembly tasks. Extensive comparisons of the different demonstration methods have been performed and the approaches have been evaluated in terms of teaching time, ease of use, and path length.

关键词： flexible manufacturing assembly programming by demonstration system integration

来源：评论

学校读者我要写书评

暂无评论

Enhanced Performance Real-Time Industrial Robot programming by demonstration using Stereoscopic Vision and an IMU sensor

Enhanced Performance Real-Time Industrial Robot Programming ...

引用

IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Pinto, Vitor H. Amorim, Antonio Rocha, Luis Moreira, Antonio P. Univ Porto FEUP Fac Engn Porto Portugal Ctr Robot Ind & Intelligent Syst INESCTEC Porto Portugal

ISBN: (纸本)9781728170787

Nowadays, industrial robots are still commonly programmed using essentially off-line tools, such as is the case of structured languages or simulated environments. This is a very time-consuming process, which necessarily requires the presence of an experienced programmer with technical knowledge of the set-up to be used, as well as a concept and a complete definition of the details associated with the operations. Moreover, considering some industrial applications such as coating, painting, and polishing, which commonly require the presence of highly skilled shop floor operators, the translation of this human craftsmanship into robot language using the available programming tools is still a very difficult task. In this regard, this paper presents a programming by demonstration solution, that allows a skilled shop floor operator to directly teach the industrial robot. The proposed system is based on the 6D Mimic innovative solution, endowed with an IMU sensor as to enable the system to tolerate temporary occlusions of the 6D Marker. Results show that, in the event of an occlusion, a reliable and highly accurate pose estimation is achieved using the IMU data. Furthermore, the selected IMU was a low-cost model, to not severely increase the 6D Mimic cost, despite lowering the quality of the readings. Even in these conditions, the developed algorithm was able to produce high-quality estimations during short time occlusions.

关键词： programming by demonstration Agile Robotic Systems Industry 4.0 IMU

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：