2013
DOI: 10.1115/1.4025966
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Magnetorheologically Damped Compliant Foot for Legged Robotic Application

Abstract: This paper presents an innovative solution for bounce reduction between a robotic leg and the ground by means of a semi-active compliant foot. The aim of this work is to enhance the controllability and the balance of a legged robot by improving the traction between the foot tip and the ground. The compliant foot is custom-designed for quadruped walking robots and it consists of a linear spring and a magnetorheological (MR) damper. By utilizing magnetorheological technology in the damper element, the damping co… Show more

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Cited by 19 publications
(13 citation statements)
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“…The black dashed line of the top plot in Figure 9 shows how a low initial impact peak can be combined with a low settling time. While this is a very simple control law, more sophisticated modulations are possible, such as for example the skyhook controller that we implemented in Kostamo et al (2013) for a semi-active magneto-rheological damper.…”
Section: Resultsmentioning
confidence: 99%
“…The black dashed line of the top plot in Figure 9 shows how a low initial impact peak can be combined with a low settling time. While this is a very simple control law, more sophisticated modulations are possible, such as for example the skyhook controller that we implemented in Kostamo et al (2013) for a semi-active magneto-rheological damper.…”
Section: Resultsmentioning
confidence: 99%
“…The other work is the HyQ robotic leg, in which a magnetorheological (MR) damper was placed in the distal segment of the leg. The primary aim here was to dampen unwanted oscillations at touchdown by dissipating the impact kinetic energy, and thereby to improve the traction between the foot tip and the ground [84,116]. In addition, an efficient activation mechanism for the MR damper may be required to avoid hindering desired leg movements and, meanwhile, minimizing the power consumption of the damper itself [117].…”
Section: Dampingmentioning
confidence: 99%
“…The control algorithm is based on the assumed mode Lagrangian dynamic model of the system. According to the hybrid system theory [15], the dynamic of the mechanism is divided in the two different phases. In the flying phase (Fig.…”
Section: B Cosimulated Machinery Modelmentioning
confidence: 99%