Abstract
This paper discusses how to optimally design polygonal profiles of Electromagnetic Soft Actuators (ESAs) to be used in a network to achieve maximum output force with minimum energy consumption. The soft actuators work based on operating principle of solenoids but are made of intrinsically soft materials. It was, previously, confirmed that by miniaturizing the size, the amount of output force decreases for a single ESA however, by the ratio of force to volume increases. Therefore, networking small sized ESAs, would increase the output force. Initially, ESAs were made with circular cross-section profiles. However, we prove here that the shape of the cross-section profile can affect the output force. A polygonal shape with fewer sides would result in higher output force for a single ESA. However, with a network of ESAs, another parameter, packing density, plays an important role in the output force. Our optimization results suggest that even though triangular cross-section profiles lead to the highest amount of force for a single ESA, the best choice would be hexagonal shapes when they are networked.
Highlights
Physical Human–Robot Interaction, requires a technology to fabricate the robotic platform that is fundamentally different from industrial robots [1]
The flux charge density was measured by Magnetic Field Instrument (MFI), a device used to measure the magnetic field or flux around permanent magnets, coils, and electrical devices
The flux charge density was measured by Magnetic Field Instrument (MFI), a device used to evaluate the magnetic field or flux produced around permanent magnets, solenoids, and electrical devices
Summary
Physical Human–Robot Interaction (pHRI), requires a technology to fabricate the robotic platform that is fundamentally different from industrial robots [1]. These platforms are supposed to physically interact with the soft tissues of the human body, where exerting forces outside the tissues structural limitations would lead to medical hazards. Industrial robots are designed for fast and accurate position control applications where everything about the environment is known and predictable. In pHRI, we need to take into account the uncertainties regarding the force interactions [2]. An intrinsically soft robotic platform can provide a novel and safer option for biomedical applications [3,4]
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