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DOI 10.3389/frobt.2026.1736915

Медицинская библиотека · Frontiers in robotics and AI · 2026

Fibrous contextual embodiments formed by task-invariant continuous blow spinning in dynamic environments.

Vihmar Marie, Boiko Roman, Pankratov Kadri-Ann, Kaasik Friedrich, Ojavee Kärt, Must Indrek

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Аннотация

Navigating dynamic environments is challenging for robots. While data-intensive control can guide high-level decisions, the complexity of typical natural settings, dynamic in particular, motivates offloading part of intelligent behavior to the robot's morphology. Here, we introduce an in situ, model-free melt-blown process that creates unsupported thermoplastic webs via direct environmental interaction, enabling ad hoc robotic embodiments. When spun on moving supports, fiber elasticity causes support motion to align fibers and homogenize the web rather than breaking it, yielding ∼60% reversible strain and stretch to ∼1,000% at ultimate rupture. We illustrate task-invariant fiber spinning in several task contexts relevant to complex environments: creating mobility pathways in moving environments, immobilizing moving objects, sampling discrete materials, and capturing resources (oil-soaked sponges). Unlike pre-fabricated embodiments or deployable effectors, in situ spun fibrous bodies emerge from environmental dynamics, thus the web is not an environment-referenced static object but functions as an interface that incorporates environmental information through interaction. This spiderweb-inspired, temporally and spatially scalable approach allows robots to extend, adjust, and repair their physical architecture in response to changing conditions, leading to robots that morph context-specific components and engage informational and material resources in the environment to tackle open-ended tasks beyond their initial physical architecture.

Для цитирования: Vihmar Marie, Boiko Roman, Pankratov Kadri-Ann, Kaasik Friedrich, Ojavee Kärt, Must Indrek. Fibrous contextual embodiments formed by task-invariant continuous blow spinning in dynamic environments.. Frontiers in robotics and AI. 2026. DOI: 10.3389/frobt.2026.1736915.
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