Add project "Training Robot Motions Using Slicer Images" to "PW45_2026_Boston"

PW45_2026_Boston/Projects/TrainingRobotMotionsUsingSlicerImages/README.md

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+---
+layout: pw45-project
+
+permalink: /:path/
+
+project_title: Training Robot Motions Using Slicer Images
+category: IGT and Training
+presenter_location: 
+
+key_investigators:
+
+- name: Taewoo Yoon
+  affiliation: AIRS Inc
+  country: Republic of Korea
+
+- name: Joonho Seo
+  affiliation: Korea Institute of Machinery Materials
+  country: Republic of Korea
+
+---
+
+# Project Description
+
+<!-- Add a short paragraph describing the project. -->
+
+
+3D Slicer can function as a tool to display real-time object movements in a 3D view. 
+We intend to utilize this **3D view as training data for robotic motion**.
+The 3D Slicer view will function just like a real camera mounted on the robot.
+Furthermore, it will allow us to build **custom simulation environments to generate and train on virtual data**.
+
+<img width="1139" height="311" alt="Image" src="https://github.com/user-attachments/assets/09d40dbd-0033-45a7-8e0d-324c90201013" />
+
+
+
+## Objective
+
+<!-- Describe here WHAT you would like to achieve (what you will have as end result). -->
+
+
+- Establishing a pipeline to integrate 3D Slicer's visual data with robot joint data for advanced policy learning and real-time inference.
+- Establishing an environment dedicated to generating and training on synthetic simulation data.
+
+<img width="1334" height="530" alt="Image" src="https://github.com/user-attachments/assets/9b099b3d-69ae-4c0a-b26b-c2931b94ead2" />
+
+
+
+## Approach and Plan
+
+<!-- Describe here HOW you would like to achieve the objectives stated above. -->
+
+
+1. Establishing an environment to track an object rigidly coupled with the robot in the 3D view, ensuring its pose updates dynamically in accordance with the robot's motion.
+2. Capture the 3D view for a specified number of frames while simultaneously acquiring the corresponding robot joint data.
+3. Train the policy based on the training dataset created in step 2.
+4. After training the policy, inferred joint positions are fed as control commands into either a simulation tool or physical robot.
+5. Input the 3D Slicer view into the trained model for inference.
+6. Feed the inferred joint position into either the simulation tool or physical robot, and sequentially input the updated 3D Slicer view as the next state input as the robot moves.
+
+
+
+## Progress and Next Steps
+
+<!-- Update this section as you make progress, describing of what you have ACTUALLY DONE.
+     If there are specific steps that you could not complete then you can describe them here, too. -->
+
+
+1. Describe specific steps you **have actually done**.
+
+
+
+
+# Illustrations
+
+<!-- Add pictures and links to videos that demonstrate what has been accomplished. -->
+
+
+_No response_
+
+
+
+# Background and References
+
+<!-- If you developed any software, include link to the source code repository.
+     If possible, also add links to sample data, and to any relevant publications. -->
+
+
+_No response_
+