ArticleBiomimetics (Basel, Switzerland)2025
Design and Control of Bio-Inspired Joints for Legged Robots Driven by Shape Memory Alloy Wires.
Article in Biomimetics (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- Recurrent Neural Networks with Integrated Gradients Explanation for Predicting the Hysteresis Behavior of Shape Memory Alloys.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
3 authors.
Funding
Abstract
Bio-inspired joints play a pivotal role in legged robots, directly determining their motion capabilities and overall system performance. While shape memory alloy (SMA) actuators present superior power density and silent operation compared to conventional electromechanical drives, their inherent nonlinear hysteresis and restricted strain capacity (typically less than 5%) limit actuation range and control precision. This study proposes a bio-inspired joint integrating an antagonistic actuator configuration and differential dual-diameter pulley collaboration, achieving amplified joint stroke (±60°) and bidirectional active controllability. Leveraging a comprehensive experimental platform, precise reference input tracking is realized through adaptive fuzzy control. Furthermore, an SMA-driven bio-inspired leg is developed based on this joint, along with a motion retargeting framework to map human motions onto the robotic leg. Human gait tracking experiments conducted on the leg platform validate its motion performance and explore practical applications of SMA in robotics.
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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.