Morphological computation represents a paradigm shift in robotics, where the physical structure and material properties of a robot contribute significantly to its functionality. Unlike traditional rigid robotics, which rely heavily on centralized control systems, soft robotics leverages material properties to offload computational tasks to the body itself. This approach is particularly advantageous in bio-inspired systems, where adaptability and resilience are paramount.
Shape-changing materials, such as liquid crystal elastomers (LCEs), shape-memory alloys (SMAs), and hydrogels, enable robots to exhibit adaptive behaviors without complex electronic control. These materials respond to environmental stimuli—such as temperature, light, or humidity—by altering their shape or stiffness, effectively embedding computation within their morphology.
While much research has focused on locomotion and grasping, several understudied applications of morphological computation hold promise for advancing soft robotics.
Morphological computation can enable robots to sense and adapt to their surroundings passively. For example, a soft robot embedded with LCEs could autonomously align itself with a light source, mimicking phototropism in plants. This eliminates the need for external sensors and reduces energy consumption.
Materials like self-healing polymers can repair minor damage without human intervention. When combined with morphological computation, these materials allow robots to recover functionality after sustaining cuts or punctures, enhancing their durability in unpredictable environments.
By leveraging phase-changing materials, robots can store and release mechanical energy through latent heat transitions. This approach is particularly useful in underwater robotics, where energy efficiency is critical for long-duration missions.
The octopus exemplifies morphological computation, using its muscular hydrostat structure to achieve complex movements without a rigid skeleton. Researchers have developed soft robots that mimic this behavior using pneumatically actuated elastomers, demonstrating how material properties can simplify control algorithms.
Some robots emulate plant growth by extending their bodies through additive manufacturing or material deposition. These systems can navigate cluttered environments by growing around obstacles, a capability enabled by shape-changing materials that respond to external forces.
Despite its potential, morphological computation in soft robotics faces several challenges:
The understudied applications of morphological computation—such as environmental adaptation, self-healing, and energy-efficient actuation—highlight the untapped potential of shape-changing materials in soft robotics. Future research should focus on overcoming material limitations and developing scalable fabrication techniques to bring these bio-inspired systems into real-world applications.