Experimental verification of soft-robot gaits evolved using a lumped dynamic model

Saunders, Frank; Golden, Ethan; White, Robert D.; Rife, Jason

doi:10.1017/s0263574711000014

Cited by 28 publications

(16 citation statements)

References 28 publications

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“…Similar approaches, mostly focused on the evolution of neural control systems, are reported in [37] [38] [39]. Some robotics works have focused on evolving gaits for fixed soft robots [40]. Others have evolved control and stiffness properties for fixed morphologies embedding flexible elements [41] [42], which were in some cases experimentally validated.…”

Section: Objectivementioning

confidence: 98%

Evolving Soft Locomotion in Aquatic and Terrestrial Environments: Effects of Material Properties and Environmental Transitions

et al. 2018

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Designing soft robots poses considerable challenges; automated design approaches may be particularly appealing in this field, as they promise to optimize complex multimaterial machines with very little or no human intervention. Evolutionary soft robotics is concerned with the application of optimization algorithms inspired by natural evolution to let soft robots (both their morphologies and controllers) spontaneously evolve within physically realistic simulated environments, figuring out how to satisfy a set of objectives defined by human designers. In this article, a powerful evolutionary system is put in place to perform a broad investigation on the free-form evolution of simulated walking and swimming soft robots in different environments. Three sets of experiments are reported, tackling different aspects of the evolution of soft locomotion. The first two explore the effects of different material properties on the evolution of terrestrial and aquatic soft locomotion: particularly, we show how different materials lead to the evolution of different morphologies, behaviors, and energy-performance trade-offs. It is found that within our simplified physics world, stiffer robots evolve more sophisticated and effective gaits and morphologies on land, while softer ones tend to perform better in water. The third set of experiments starts investigating the effect and potential benefits of major environmental transitions (land↔water) during evolution. Results provide interesting morphological exaptation phenomena and point out a potential asymmetry between land→water and water→land transitions: while the first type of transition appears to be detrimental, the second one seems to have some beneficial effects.

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Section: Objectivementioning

confidence: 98%

Evolving Soft Locomotion in Aquatic and Terrestrial Environments: Effects of Material Properties and Environmental Transitions

et al. 2018

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“…There are previous literatures which have extensively studied the gripping and biomechanics of prolegs of different types of caterpillars. [33][34][35][36][37][38][39] The prolegs are essential for inching and crawling locomotion as described by Van Griethuijsen and Trimmer. 35 However, a coordination of proleg grip and re-lease with a wave-like muscle activity is required for forward or turning movement.…”

Section: Inherent Friction Controlmentioning

confidence: 99%

A Fully Three-Dimensional Printed Inchworm-Inspired Soft Robot with Magnetic Actuation

2019

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In the field of robotics, researchers are aiming to develop soft or partially soft bodied robots that utilize the motion and control system of various living organisms in nature. These robots have the potential to be robust and versatile, even safer for human interaction compared to traditional rigid robots. Soft robots based on biomimetic principles are being designed for real life applications by paying attention to different shape, geometry, and actuation systems in these organisms that respond to surrounding environments and stimuli. Especially, caterpillars or inchworms have garnered attention due to their soft compliant structure and crawling locomotion system making them ideal for maneuvering in congested spaces as a transport function. Currently, there are two major challenges with design and fabrication of such soft robots: using an efficient actuation system and developing a simple manufacturing process. Different actuation systems have been explored, which include shape memory alloy based coils and hydraulic and pneumatic actuators. However, the intrinsic limitations due to overall size and control system of these actuators prevent their integration in flexibility, lightweight, and compact manner, limiting practical and untethered applications. In comparison, magnetic actuation demonstrates simple wireless noncontact control. In terms of manufacturing process, additive manufacturing has emerged as an effective tool for obtaining structural complexity with high resolution, accuracy, and desired geometry. This study proposes a fully three-dimensional (3D) printed, monolithic, and tetherless inchworminspired soft robot that uses magnetic actuation for linear locomotion and crawling. Its structure is multimaterial heterogeneous particle-polymer composite with locally programmed material compositions. This soft robot is directly printed in one piece from a 3D computer model, without any manual assembly or complex processing steps, and it can be controlled by an external wireless force. This article presents its design and manufacturing with the novel magnetic field assisted projection stereolithography technique. Analytical models and numerical simulations of the crawling locomotion of the soft robot are also presented and compared with the experimental results of the 3D printed prototype. The overall locomotion mechanism of the magnetically actuated soft robot is evaluated with friction tests and stride efficiency analysis.

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“…The prohibitive computational cost of direct optimization on physical robots has led some researchers to envisage full optimization processes in simulation [53]. A first attempt to deal with the reality gap is to build more accurate simulation models.…”

Section: B Simulation-based Optimizationmentioning

confidence: 99%

The Transferability Approach: Crossing the Reality Gap in Evolutionary Robotics

Koos

Mouret

Doncieux

2013

IEEE Trans. Evol. Computat.

216

184

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Abstract-The reality gap, that often makes controllers evolved in simulation inefficient once transferred onto the physical robot, remains a critical issue in Evolutionary Robotics (ER). We hypothesize that this gap highlights a conflict between the efficiency of the solutions in simulation and their transferability from simulation to reality: the most efficient solutions in simulation often exploit badly modeled phenomena to achieve high fitness values with unrealistic behaviors. This hypothesis leads to the Transferability approach, a multi-objective formulation of ER in which two main objectives are optimized via a Pareto-based Multi-Objective Evolutionary Algorithm: (1) the fitness and (2) the transferability, estimated by a simulation-to-reality (STR) disparity measure. To evaluate this second objective, a surrogate model of the exact STR disparity is built during the optimization. This Transferability approach has been compared to two realitybased optimization methods, a noise-based approach inspired from Jakobi's minimal simulation methodology and a local search approach. It has been validated on two robotic applications: 1) a navigation task with an e-puck robot; 2) a walking task with an 8-DOF quadrupedal robot. For both experimental set-ups, our approach successfully finds efficient and well-transferable controllers only with about ten experiments on the physical robot.

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Experimental verification of soft-robot gaits evolved using a lumped dynamic model

Cited by 28 publications

References 28 publications

Evolving Soft Locomotion in Aquatic and Terrestrial Environments: Effects of Material Properties and Environmental Transitions

Evolving Soft Locomotion in Aquatic and Terrestrial Environments: Effects of Material Properties and Environmental Transitions

A Fully Three-Dimensional Printed Inchworm-Inspired Soft Robot with Magnetic Actuation

The Transferability Approach: Crossing the Reality Gap in Evolutionary Robotics

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