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#motor-control News & Analysis

4 articles tagged with #motor-control. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

4 articles
AINeutralarXiv – CS AI · Jun 196/10
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Bidirectional Tutoring for Developmental Motor Learning in Robots: Co-Developed Interaction Dynamics Support Stable Learning

Researchers demonstrate that bidirectional tutoring—where robots and tutors dynamically adapt to each other—produces more consistent and generalizable motor learning compared to traditional unidirectional instruction. Using a free-energy-principle neural network with generative replay, experiments with a humanoid robot showed bidirectional interaction fostered stable behavioral patterns and reduced dependency on tutor guidance over time.

AINeutralarXiv – CS AI · Jun 196/10
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Movement Primitives in Robotics: A Comprehensive Survey

This arXiv survey provides a comprehensive overview of movement primitives in robotics—elementary building blocks of motion that enable autonomous systems to perform complex tasks by learning from human demonstrations. The research synthesizes frameworks spanning decades of development, examining how movement primitives can encode trajectories, incorporate spring-damper dynamics, probabilistic methods, and neural networks to address real-world robotic control challenges.

AINeutralarXiv – CS AI · Jun 106/10
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RoboNaldo: Accurate, Stable and Powerful Humanoid Soccer Shooting via Motion-Guided Curriculum Reinforcement Learning

RoboNaldo, a motion-guided curriculum reinforcement learning framework, enables humanoid robots to perform accurate soccer shots with significantly improved stability and power compared to prior approaches. The system uses a three-stage training process that progresses from mimicking human motion to adapting kicks for varied ball positions and moving targets, achieving real-world performance on a Unitree G1 robot with shot errors under 1 meter from 3 meters away.