AI & ML
A Unified Fractal Impedance Control Framework
arXiv eess.SY0 views
arXiv:2611.08009v1 Announce Type: cross Abstract: Physical human--robot interaction requires controllers capable of maintaining intrinsically bounded interactions with the environment. The Fractal Impedance Controller (FIC) has been proven to guarantee these safety characteristics by design. This paper introduces the robotic implementation and experimental validation of its most advanced architecture: the Harmonic-Passive Motion Paradigm (H-PMP), an evolution of the Passive Motion Paradigm designed to mimic human-like interaction. Furthermore, we present a unified framework for FIC deployment, supported by an open-source software suite featuring ROS2, MuJoCo, and physical hardware integrations. Through three experiments conducted on a Kinova Gen3 arm (trajectory tracking, a wall press with sudden loss of contact, and learning-by-demonstration) we compare the H-PMP against earlier FIC architectures. The results demonstrate that the H-PMP achieves a seamless trade-off between admittance and impedance behaviours. This makes it ideal for deployment in unstructured environments, enabling the robot to transition between interaction modes with no computational overhead.
Source:https://arxiv.org/abs/2611.08009PreviousOn the Spectral Dependence of Decentralized Stochastic Gradient TrackingNextWhen Imperfect Automated Fact-Checking Backfires: Social Learning in the Presence of Misinformation
Related posts
AI spend flatlined at +1.5% as Anthropic's $2T IPO shrinks
0dev.to Discuss

osFoundry का Maestro क्या करता है, एक AI चैट जो अपना हर कदम दिखाती है
0dev.to Productivity
![[Part 3] Your first steps in Computer Vision on AWS: deploying models for an ASL recognition app](https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fujtow25j4x4xr644q5s9.png)
[Part 3] Your first steps in Computer Vision on AWS: deploying models for an ASL recognition app
0dev.to Machine Learning
Perplexity Teammates Turns AI Into Coworkers That Don't Clock Out
0dev.to Machine Learning
Weight-Space Programming: When LLMs Learn to Read and Rewrite Neural Network Weights
0dev.to Machine Learning
Salesforce's Koa Decisions: One Step, One Answer, No Paragraph
0dev.to Machine Learning