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Elastic energy storage in leaf springs for a lever-arm based Variable Stiffness Actuator
The increasing use of Variable Stiffness Actuators (VSAs) in robotic joints is helping robots to meet the demands of human-robot interaction, requiring high safety and adaptability. The key feature of a VSA is the ability to exploit internal elastic elements to obtain a variable output stiffness. These allow the joints to store mechanical energy supplied through interaction with the environment and make the system more robust, efficient, and safe. This paper discusses the design of leaf springs for a sub-class of VSAs that use variable lever arm ratios as means to change their output stiffness. Given the trade-off between compactness and the maximum energy storage capacity, the internal springs’ dimensions and material choice are assessed through a theoretical analysis and practical experiments.
- Aalborg University Library (AUB) Aalborg Universitet Research Portal Denmark
- University of Twente Netherlands
- Aalborg University Library (AUB) Denmark
- Aalborg University Denmark
- Aalborg University Denmark
Energy storage, EWI-27577, METIS-320937, Stress, Springs, Design methodology, IR-103141, manipulators, Robots, Actuators, Force
Energy storage, EWI-27577, METIS-320937, Stress, Springs, Design methodology, IR-103141, manipulators, Robots, Actuators, Force
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).17 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
