How do soft robots mimic biological movements?

Soft robots mimic biological movements by combining compliant materials, distributed actuation, and sensor-driven control to reproduce the continuous, adaptive motions of muscles, skin, and soft tissues. Researchers emphasize that the key is not copying anatomy exactly but emulating functional principles such as compliance, redundancy, and variable stiffness. Cecilia Laschi at Scuola Superiore Sant'Anna has demonstrated how octopus arms inspire continuum manipulators that bend, elongate, and conform to objects without rigid joints, showing that soft morphology itself performs part of the control traditionally handled by rigid structures and complex algorithms.

Materials and actuation

Soft robots typically use elastomers, hydrogels, textiles, and other deformable media that behave more like biological tissue than metal. Actuation methods are chosen to reproduce muscle-like contraction and extension. Pneumatic networks that inflate to produce bending and extension have been widely adopted because they can generate large strains at low weight; George M. Whitesides at Harvard University and colleagues helped popularize soft pneumatic actuators that achieve complex deformations through patterned internal channels. Electroactive polymers and dielectric elastomers change shape when voltage is applied, enabling fast responses in small devices. Shape-memory alloys and hydrogels offer temperature or chemistry-driven actuation that can mimic slow biological processes such as growth or swelling. Magnetic and cable-driven systems provide alternatives where electrical or pneumatic infrastructure is limited.

Sensing and control

Biological systems use dense sensory feedback across tissues to coordinate movement. Soft robots recreate this with embedded stretch sensors, pressure sensors, and proprioceptive elements distributed through the body. Daniela Rus at Massachusetts Institute of Technology highlights the importance of co-designing the body and controller so that mechanical intelligence in the material reduces computational burden. Instead of rigid-body inverse dynamics, many soft systems use model-free learning, morphological computation, or simplified continuum models that exploit the robot’s natural dynamics to perform tasks like grasping, locomotion, or undulatory swimming.

Relevance, causes, and consequences

Mimicking biological movement makes robots safer for human environments, more effective in unstructured terrain, and better suited for delicate tasks such as medical devices or ecological monitoring. The cause of this trend is twofold: biologically inspired design offers technical advantages in adaptability, and advances in soft materials and fabrication, including 3D printing and soft lithography, make production feasible. Consequences include shifts in applications and regulation. Soft prosthetics and surgical tools can reduce tissue damage, but they require new testing standards and clinical validation pathways. Environmental consequences are mixed. Soft robots that enable less-invasive monitoring of fragile ecosystems can aid conservation, a point stressed by field projects using soft underwater vehicles, but many elastomers are not biodegradable, raising lifecycle concerns that researchers and manufacturers must address.

Human and territorial nuances matter for adoption. Healthcare systems in different countries will regulate soft medical robots differently, affecting access. Communities that depend on fisheries or coral reef tourism may welcome soft underwater robots for non-destructive surveys, while societies with limited technical infrastructure may prioritize low-power actuation methods. Continuing collaboration between materials scientists, roboticists, clinicians, and local stakeholders will determine how effectively soft robotics can translate biological principles into practical, responsible technologies.