ArticleInnovation (Cambridge (Mass.))2024
An intelligent spinal soft robot with self-sensing adaptability.
Article in Innovation (Cambridge (Mass.)), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- A foldable small-scale soft electromagnetic robot for multimodal navigation in confined and unstructured environments.Nature communications · 2026Article
- A soft perceptive multimodal locomotion robot via double-helix fiber-reinforced artificial muscles.Innovation (Cambridge (Mass.)) · 2026Article
- Magnetically controlled multimodal motion for environmentally adaptive soft millirobots with transformable wheel-leg morphology.Innovation (Cambridge (Mass.)) · 2026Article
- An Insect-Scale Untethered Piezoelectric Robot with Multiple Biomimetic Features.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Asymmetries-induced nonlinear dynamic behaviors enable versatile modulation strategy for insect-scale robotics.Science advances · 2025Article
- Robotic ray driven by periodic ring snapping.Innovation (Cambridge (Mass.)) · 2025Article
- Breaking Stiffness-Tunability Trade-offs in Metamaterials: a Minimal Surface Guided Hybrid Lattice Strategy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Intelligent excitation adaptability for full-spectrum real-time vibration isolation.Communications engineering · 2025Article
- A Multimodal Amphibious Robot Driven by Soft Electrohydraulic Flippers.Cyborg and bionic systems (Washington, D.C.) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Self-sensing adaptability is a high-level intelligence in living creatures and is highly desired for their biomimetic soft robots for efficient interaction with the surroundings. Self-sensing adaptability can be achieved in soft robots by the integration of sensors and actuators. However, current strategies simply assemble discrete sensors and actuators into one robotic system and, thus, dilute their synergistic and complementary connections, causing low-level adaptability and poor decision-making capability. Here, inspired by vertebrate animals supported by highly evolved backbones, we propose a concept of a bionic spine that integrates sensing and actuation into one shared body based on the reversible piezoelectric effect and a decoupling mechanism to extract the environmental feedback. We demonstrate that the soft robots equipped with the bionic spines feature locomotion speed improvements between 39.5% and 80% for various environmental terrains. More importantly, it can also enable the robots to accurately recognize and actively adapt to changing environments with obstacle avoidance capability by learning-based gait adjustments. We envision that the proposed bionic spine could serve as a building block for locomotive soft robots toward more intelligent machine-environment interactions in the future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.