Bio-Inspired Soft Robotics: AI-Driven Morphological Adaptation for Terrain Navigation

Abstract

The idea of soft robotics has turned out to be one of the most promising areas of modern robotics due to natural flexibility, safety, and naturalistic movement, like natural creatures. The present study will explore the idea of implementing the concept of artificial intelligence (AI) on bio-inspired soft robots to enable morphological adaptation to navigate through adverse environments. The article identifies the advantages of actuator flexibility, compliant mechanisms, and biological influenced body structures that bring enormous dividends in the spheres where the conventional rigid robots would be rendered useless. To be capable of deforming, squeeze, stretch and hold on to objects in a manner that they can navigate through rough surfaces, squeeze in tight crevices and dynamic response to more unpredictable challenges, soft robots are becoming inspired by things like octopuses, caterpillars, worms and snakes. The abstract also explains how the AI techniques, particularly the reinforcement techniques and deep neural networks, and adaptive control algorithms allow robots to adaptively change body shape and stiffness in real-time, increasing their mobility and survivability when exploring or executing rescue missions.Furthermore, the intelligence and data-driven decision-making based on sensors can aid the soft robots to recognize the state of the terrain and modify the movement plans. Their capabilities are enhanced by such capabilities based on AI, which enables them to operate more effectively under such harsh conditions as rubble, mud, in underwater environments, and in fallen buildings. It is emphasized in the study that morphological adaptation is not merely a mechanical ability, but a complex system, which, in turn, presupposes perception, learning, and responsive actuation. The paper concludes that intelligent soft robotics, consisting of bio-inspired design and AI control models, is an innovational solution to the next-generation robotic mobility that can perform its tasks in hazardous, unpredictable, or inaccessible surrounding where traditional robots fail. The work will be added to the evolution of the adaptive soft robotics and the creation of a guideline of the evolution in the sphere of the navigation of the terrain.