Towards Open Loop Control of Soft Multistable Grippers From Energy Based Modelling
Abstract
Soft robotics is concerned with the modeling and designing of devices fabricated from materials with low Young’s moduli—much less than that of metal— that mimic the input/output operation and physical task utility of robotics. The inherent compliance of soft robots lends these devices an adaptability and a capacity for human-machine interaction beyond that of conventional robotics. Multistable soft robotic grippers are a subset of the technology at the intersection of soft robotics and multistable structures. Multistable structures are continuum systems that exhibit more than one statically stable state, each associated with a strain energy minimum. The existence of these energetic minima allows the structures to adopt different stable configurations that can provide a reference point for open loop control schemes. Multistable soft robotics takes advantage of both the adaptability of soft robotics and the potential for simplified control of multistable structures. Achieving simplified control for soft robotics is a necessary milestone in creating functional and applied soft robots. This work presents a means for simple open-loop control of a multistable soft robotic gripper that is adaptable, controllable, and robust. The behavior is illustrated through a gripper geometry described by specific design parameters resulting in a near infinite design space. An analytical model based on lumped parameter springs is derived, allowing us to search the design space in a tractable fashion. Specifically, we predict the system’s stable states for any given design instance by searching for local minima in the energy landscape formed by a spring lattice representation of our device. The lattice is composed of linear, bistable, and torsional springs—each of which contributes to the energy landscape of the system. We validate our model against Finite Element simulations of our device, showing good agreement with the proposed model. The aptitude of the model sheds light on the fundamental mechanics of our soft robotic gripper topology, laying the foundation for efficient design optimization and simplified control of soft robots.
Degree
M.Sc.
Advisors
Arrieta, Purdue University.
Subject Area
Robotics|Mechanics|Applied physics|Design|Energy|Physics|Polymer chemistry|Therapy
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