Trajectory Optimization for Thermally-Actuated Soft Planar Robot Limbs

Wertz, Anthony; Sabelhaus, Andrew P.; Majidi, Carmel

doi:10.1109/robosoft54090.2022.9762226

Cited by 7 publications

(13 citation statements)

References 34 publications

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“…These would not be available during online prediction scenarios, as would be the case for feedback control. However, we consider these tests to be valid, since prior work has shown that the temperature of SMA wires can be predicted reasonably well from Joule heating models ( Wertz et al, 2022 ) and that LSTM networks may also be able to predict temperature itself ( Luong et al, 2021 ). A possible direction for future work is therefore predicting temperature alongside bending angle.…”

Section: Discussionmentioning

confidence: 99%

“…The limb is designed for planar motions only, reducing the dimensionality of the state space in order to test algorithmic approaches to modeling and control. An earlier version of this limb was used in Wertz et al, 2022 , and this article extends and details the fabrication procedure for the in-situ embedded temperature sensor.…”

Section: Methodsmentioning

confidence: 99%

“…The limb is actuated using SMA coils that are activated through electrical current and Joule heating. We hypothesize that temperature is a reasonable surrogate for full thermal actuator state due to the prior successes of Ge et al (2021) and Wertz et al (2022) in tracking the behavior of SMA-based actuators. Our framework includes a fabrication method to securely and robustly attach a compact temperature sensor to a highly-dynamic SMA wire, alongside a neural network-based model that captures hysteresis in sensor data versus limb pose.…”

Section: Introductionmentioning

confidence: 99%

“…Then we train and validate the model using open-loop simulations ( Figure 1C ). For comparison, we perform a least-squares fit on the same data, as was used in Wertz et al, 2022 , and show that our neural network makes predictions possible using PWM duty cycles only. Our validation shows close alignment with hardware data when measurements from all of the sensors are included.…”

Section: Introductionmentioning

confidence: 99%

“…Feedback has been used for soft electrothermal and shape memory actuators, but when performed with embedded sensing only, has been limited to model-free approaches ( Elahinia and Ashrafiuon 2002 ; Ma et al, 2004 ; Kent et al, 2020 ; Kotikian et al, 2021 ) or simplistic models without actuator dynamics ( Patterson et al, 2022 ). However, many benefits to modeling exist in the context of open-loop motion generation, including a-priori trajectory optimization ( Wertz et al, 2022 ) that avoids the artificially-induced stiffness imposed by feedback control ( Della Santina et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

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In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

et al. 2022

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Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network-based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 min) with little drift. Prediction errors are on the order of the soft deflection sensor’s accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

et al. 2022

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Liquid Crystal Elastomer with Integrated Soft Thermoelectrics for Shape Memory Actuation and Energy Harvesting

et al. 2022

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Liquid crystal elastomers (LCEs) have attracted tremendous interest as actuators for soft robotics due to their mechanical and shape memory properties. However, LCE actuators typically respond to thermal stimulation through active Joule heating and passive cooling, which make them difficult to control. In this work, LCEs are combined with soft, stretchable thermoelectrics to create transducers capable of electrically controlled actuation, active cooling, and thermal‐to‐electrical energy conversion. The thermoelectric layers are composed of semiconductors embedded within a 3D printed elastomer matrix and wired together with eutectic gallium–indium (EGaIn) liquid metal interconnects. This layer is covered on both sides with LCE, which alternately heats and cools to achieve cyclical bending actuation in response to voltage‐controlled Peltier activation. Moreover, the thermoelectric layer can harvest energy from thermal gradients between the two LCE layers through the Seebeck effect, allowing for regenerative energy harvesting. As demonstrations, first, closed‐loop control of the transducer is performed to rapidly track a changing actuator position. Second, a soft robotic walker that is capable of walking toward a heat source and harvesting energy is introduced. Lastly, phototropic‐inspired autonomous deflection of the limbs toward a heat source is shown, demonstrating an additional method to increase energy recuperation efficiency for soft systems.

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Soft robotics informs how an early echinoderm moved

Desatnik,

Patterson,

Gorzelak

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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The transition from sessile suspension to active mobile detritus feeding in early echinoderms (c.a. 500 Mya) required sophisticated locomotion strategies. However, understanding locomotion adopted by extinct animals in the absence of trace fossils and modern analogues is extremely challenging. Here, we develop a biomimetic soft robot testbed with accompanying computational simulation to understand fundamental principles of locomotion in one of the most enigmatic mobile groups of early stalked echinoderms—pleurocystitids. We show that these Paleozoic echinoderms were likely able to move over the sea bottom by means of a muscular stem that pushed the animal forward (anteriorly). We also demonstrate that wide, sweeping gaits could have been the most effective for these echinoderms and that increasing stem length might have significantly increased velocity with minimal additional energy cost. The overall approach followed here, which we call “Paleobionics,” is a nascent but rapidly developing research agenda in which robots are designed based on extinct organisms to generate insights in engineering and evolution.

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Trajectory Optimization for Thermally-Actuated Soft Planar Robot Limbs

Cited by 7 publications

References 34 publications

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

Liquid Crystal Elastomer with Integrated Soft Thermoelectrics for Shape Memory Actuation and Energy Harvesting

Soft robotics informs how an early echinoderm moved

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