Refine
Year of publication
- 2024 (67)
- 2023 (94)
- 2022 (136)
- 2021 (136)
- 2020 (169)
- 2019 (196)
- 2018 (169)
- 2017 (154)
- 2016 (157)
- 2015 (162)
- 2014 (161)
- 2013 (171)
- 2012 (162)
- 2011 (183)
- 2010 (181)
- 2009 (179)
- 2008 (150)
- 2007 (137)
- 2006 (129)
- 2005 (122)
- 2004 (150)
- 2003 (95)
- 2002 (123)
- 2001 (103)
- 2000 (102)
- 1999 (109)
- 1998 (98)
- 1997 (96)
- 1996 (81)
- 1995 (78)
- 1994 (87)
- 1993 (59)
- 1992 (54)
- 1991 (29)
- 1990 (39)
- 1989 (44)
- 1988 (56)
- 1987 (32)
- 1986 (19)
- 1985 (33)
- 1984 (22)
- 1983 (20)
- 1982 (29)
- 1981 (20)
- 1980 (36)
- 1979 (24)
- 1978 (34)
- 1977 (14)
- 1976 (13)
- 1975 (12)
- 1974 (3)
- 1973 (2)
- 1972 (2)
- 1971 (1)
- 1968 (1)
Institute
- Fachbereich Medizintechnik und Technomathematik (1575)
- Fachbereich Elektrotechnik und Informationstechnik (715)
- IfB - Institut für Bioengineering (567)
- Fachbereich Energietechnik (563)
- Fachbereich Chemie und Biotechnologie (541)
- INB - Institut für Nano- und Biotechnologien (533)
- Fachbereich Luft- und Raumfahrttechnik (484)
- Fachbereich Maschinenbau und Mechatronik (272)
- Fachbereich Wirtschaftswissenschaften (209)
- Solar-Institut Jülich (161)
Has Fulltext
- no (4735) (remove)
Language
- English (4735) (remove)
Document Type
- Article (3194)
- Conference Proceeding (1065)
- Part of a Book (197)
- Book (146)
- Conference: Meeting Abstract (34)
- Doctoral Thesis (32)
- Patent (25)
- Other (10)
- Report (10)
- Conference Poster (5)
Keywords
- Gamification (6)
- avalanche (6)
- Additive manufacturing (5)
- Earthquake (5)
- Enterprise Architecture (5)
- Industry 4.0 (5)
- MINLP (5)
- Natural language processing (5)
- solar sail (5)
- Additive Manufacturing (4)
The possibility of using the atomic-force microscopy as a method for detection of the analytical signal from plasticized polymeric sensor membranes was analyzed. The surfaces of cadmium-selective membranes based on two polymeric matrices were examined. The digital images were processed with multivariate image analysis techniques. A correlation was found between the surface profile of an ion-selective membrane and the concentration of the ion in solution.
Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an
industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories.
Comparison of different training algorithms for the leg extension training with an industrial robot
(2018)
In the past, different training scenarios have been developed and implemented on robotic research platforms, but no systematic analysis and comparison have been done so far. This paper deals with the comparison of an isokinematic (motion with constant velocity) and an isotonic (motion against constant weight) training algorithm. Both algorithms are designed for a robotic research platform consisting of a 3D force plate and a high payload industrial robot, which allows leg extension training with arbitrary six-dimensional motion trajectories. In the isokinematic as well as the isotonic training algorithm, individual paths are defined i n C artesian s pace by sufficient s upport p oses. I n t he i sotonic t raining s cenario, the trajectory is adapted to the measured force as the robot should only move along the trajectory as long as the force applied by the user exceeds a minimum threshold. In the isotonic training scenario however, the robot’s acceleration is a function of the force applied by the user. To validate these findings, a simulative experiment with a simple linear trajectory is performed. For this purpose, the same force path is applied in both training scenarios. The results illustrate that the algorithms differ in the force dependent trajectory adaption.