Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

State Space to Transfer Function

State Space to Transfer Function

The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:

Transfer Function to State Space

Transfer Function to State Space

State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
In an RLC...

Fluid Movement Between Compartments

Fluid Movement Between Compartments

The force applied by fluids against a surface, known as hydrostatic pressure, initiates the transfer of fluid among different compartments. Within our blood vessels, the blood's hydrostatic pressure is a result of the heart's pumping action. At the arteriolar end of capillaries, hydrostatic pressure (capillary blood pressure) exceeds the opposing colloid osmotic pressure created primarily by plasma proteins like albumin. This discrepancy in pressure propels plasma and nutrients from the...

State Space Representation

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...

Fixed Action Patterns

Fixed Action Patterns

A fixed action pattern (FAP) is a specific, hard-wired sequence of behaviors that occurs in response to an external stimulus, called a sign stimulus. The behavior is “fixed” because it is essentially unchangeable—proceeding similarly across individuals of a species every time it occurs.

Space Curves

Space Curves

A space curve describes the path followed by a particle moving through three-dimensional space. Unlike plane curves, which are confined to two coordinates, space curves require three coordinate functions. If t is a parameter, the position of the particle is represented by the vector function\begin{equation*}\mathbf{r}(t)=\langle x(t),y(t),z(t)\rangle,\end{equation*}where x(t), y(t), and z(t) are differentiable functions of t. As t varies over an interval, the endpoints of the position vectors...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Sensing the Action: Rethinking Sensor Modalities and Multi-Modal Fusion in Vision-Language-Action Models for Robotic Manipulation.

Sensors (Basel, Switzerland)·2026

Same author

Design and Validation of a Pressure-Driven Liquid Metering System with Heated PTFE Tubing for Laboratory Automation.

Sensors (Basel, Switzerland)·2026

Same author

Keyword-Conditioned Image Segmentation via the Cross-Attentive Alignment of Language and Vision Sensor Data.

Sensors (Basel, Switzerland)·2025

Same author

Scene Graph and Natural Language-Based Semantic Image Retrieval Using Vision Sensor Data.

Sensors (Basel, Switzerland)·2025

Same author

Rethinking Attention Mechanisms in Vision Transformers with Graph Structures.

Sensors (Basel, Switzerland)·2024

Same author

High-Resolution Tactile-Sensation Diagnostic Imaging System for Thyroid Cancer.

Sensors (Basel, Switzerland)·2023

Search research articles

Related Experiment Video

Updated: Jul 16, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

simDP: Sim-to-Real Transfer with Shared Action Spaces.

Chanhyuk Jung¹, Jongbin Choi², Sungkeun Yoo²

¹Department of Computer Engineering, Keimyung University, Daegu 42601, Republic of Korea.

Sensors (Basel, Switzerland)

|July 15, 2026

Summary

We introduce simDP, a framework for sim-to-real transfer, enabling diffusion policies trained in simulation to work on real robots. This approach aligns action and observation spaces, reducing the gap for efficient real-world deployment.

Keywords:

diffusion policy real-world robotics robotic manipulation shared action space sim-to-real

More Related Videos

Operation of the Collaborative Composite Manufacturing (CCM) System

Operation of the Collaborative Composite Manufacturing (CCM) System

Published on: October 1, 2019

Related Experiment Videos

Last Updated: Jul 16, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

Operation of the Collaborative Composite Manufacturing (CCM) System

Operation of the Collaborative Composite Manufacturing (CCM) System

Published on: October 1, 2019

Area of Science:

Robotics
Machine Learning
Computer Vision

Background:

Sim-to-real transfer is crucial for deploying machine learning models on physical robots.
Bridging the simulation-to-reality gap remains a significant challenge in robotics.
Diffusion policies offer promising capabilities for complex robotic tasks.

Purpose of the Study:

To propose simDP, a novel framework for effective sim-to-real transfer of diffusion policies.
To reduce the sim-to-real gap by aligning action and observation spaces.
To enable efficient deployment of simulation-trained policies on real-world robots.

Main Methods:

Reformulated action space using end-effector pose and binary gripper state for cross-domain consistency.
Utilized camera-based visual observations as the primary sensing modality.
Trained a real-world observation encoder to align with simulation-learned latent representations.

Main Results:

Achieved task completion performance comparable to, and in some cases exceeding, policies trained solely on real-world data.
Demonstrated successful object manipulation tasks using the simDP framework.
Validated the effectiveness of reusing simulation-trained action decoders with adapted real-world encoders.

Conclusions:

Reusing simulation-trained action decoders with lightweight real-world encoder adaptation is an effective strategy for controlled sim-to-real transfer.
The simDP framework facilitates efficient deployment of diffusion policies on real robots.
Further research should explore diverse tasks, environments, and robot embodiments.