Movie of the simulation results (mp4) from Gait control in a soft robot by sensing interactions with the environment using self-deformation

All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm <i>Manduca sexta</i>. This robot uses deformations of its body to detect changes in friction force on the substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback

Processing Code from Gait control in a soft robot by sensing interactions with the environment using self-deformation

All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm <i>Manduca sexta</i>. This robot uses deformations of its body to detect changes in friction force on the substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback

Movie of the experimental results (mp4) from Gait control in a soft robot by sensing interactions with the environment using self-deformation

All animals use mechanosensors to help them move in complex and changing environments. With few exceptions, these sensors are embedded in soft tissues that deform in normal use such that sensory feedback results from the interaction of an animal with its environment. Useful information about the environment is expected to be embedded in the mechanical responses of the tissues during movements. To explore how such sensory information can be used to control movements, we have developed a soft-bodied crawling robot inspired by a highly tractable animal model, the tobacco hornworm <i>Manduca sexta</i>. This robot uses deformations of its body to detect changes in friction force on the substrate. This information is used to provide local sensory feedback for coupled oscillators that control the robot's locomotion. The validity of the control strategy is demonstrated with both simulation and a highly deformable three-dimensionally printed soft robot. The results show that very simple oscillators are able to generate propagating waves and crawling/inching locomotion through the interplay of deformation in different body parts in a fully decentralized manner. Additionally, we confirmed numerically and experimentally that the gait pattern can switch depending on the surface contact points. These results are expected to help in the design of adaptable, robust locomotion control systems for soft robots and also suggest testable hypotheses about how soft animals use sensory feedback

Index of movement analysis for <i>M. sexta</i> vs. C2C12 muscle.

<p>Plot of average index of movement over time for both cell types for 3 regions per condition. Values are significant for <i>M. sexta</i> t = 16d compared to previous time points, as indicated, and t = 23d compared to previous time points, as indicated. * p<0.001.</p

Medium concentrations of metabolites tracked over time in insect and mouse C2C12 cell cultures, on a per cell basis.

<p>Glucose consumption and lactate production were analyzed for <i>M. sexta</i> control (CON, black circles) and low glucose (LG, black diamonds) conditions, along with C2C12 CON (gray squares) and LG (gray triangles) samples for comparison (A–B). Statistically different values are compared with corresponding time 0 values for glucose (A), and between <i>M. sexta</i> CON and LG for lactate (B). For amino acid analysis, C2C12 low glucose condition was omitted (C–D). * p<0.05.</p

Cell type identification within heterogeneous cultures.

<p>Histological sectioning and H&E staining of a developing embryo 19 h post-ovipositioning (A). Dark regions are cross-sections of the embryo. The rest of the egg contains yolk granules and yolk cells. Yolk cells (vitellophages) are 20–50 µm in diameter and contain a single nucleus, stained dark purple (inset, day 0). These cells are also observed in our cultures, and tend to contain a single, large lipid droplet, as shown in red by Oil Red O staining (B). Myogenic cells are the dominant population present in long-term cultures (C–D). Positive staining of myotubes for insect muscle myosin heavy chain (green) on day 48 confirms mature muscle cell identity. Additionally, sarcomeric striations are visible. Nuclear staining with DAPI (blue) reveals multinucleation Scale bars are as noted.</p

Effects of juvenile hormone (JH) mimic, methoprene, on 20HE action and cell proliferation.

<p>Phase contrast images of cells cultured in 20 ng/mL 20HE and varying levels of methoprene (A–F). Total number of nuclei and BrDU-positive nuclei on day 2 and 6 for varying methoprene concentrations (G–H). * p<0.05, ** p<0.01. Scale bars are 50 µm.</p

Schematic of embryonic <i>M. sexta</i> cell isolation process.

<p>Schematic of embryonic <i>M. sexta</i> cell isolation process.</p

<i>M. sexta</i> muscle cell viability over time.

<p>Phase contrast (A, C, E) and LIVE/DEAD staining (B, D, E) of typical cultures grown in the absence of medium changes. For LIVE/DEAD images, green staining indicates live cells and red staining indicates dead cells. Representative images taken from cultures on day 28 (A–B), day 44 (C–D), and day 75 (E–F). Scale bars are 100 µm.</p

Cryopreservation and resuscitation of <i>M. sexta</i> embryonic cells.

<p>Phase contrast images of freshly isolated (A) and resuscitated cells, after two weeks of cryopreservation, using DMSO and glycerol as cryoprotectants (B–C)). All panels show day 18 results. Scale bars are 100 µm.</p