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FRFraunhofer-Gesellschaft

Student Assistant - Learning contact-rich tasks in simulation with RL/foundational models(m/w/x)

Stuttgart
Full-timeWorking StudentOn-site

Setting up physics-based simulation environments for contact-rich assembly operations. Experience with robotics simulation, Python, C++, ROS, and PyTorch required. Freedom to implement own ideas.

Requirements

  • Enrollment in robotics, computer science, AI, or related field
  • Experience with robotics simulation environments (Isaac Sim, MuJoCo, Bullet)
  • Strong programming skills in Python, C++
  • Experience with ROS (Robot Operating System)
  • Experience with machine learning frameworks, particularly PyTorch
  • Experience in reinforcement learning methods
  • Interest/initial experience with generative AI (LLMs, VLMs)
  • Experience with robotic manipulators (beneficial)
  • Fluent English

Tasks

  • Set up physics-based simulation environments
  • Configure different simulators and robot models
  • Model contact-rich handling and assembly operations
  • Implement contact-rich assembly processes in simulation
  • Design RL-based approaches for assembly learning
  • Train RL models to learn assembly policies
  • Investigate state-of-the-art foundation models
  • Model assembly operations using foundation models
  • Generalize assembly operations with foundation models
  • Explore generative AI for skill sequence generation
  • Document developed methods and findings
  • Present methods and findings

Education

  • Currently in higher education

Languages

  • EnglishFluent

Tools & Technologies

  • Isaac Sim
  • MuJoCo
  • Bullet
  • Python
  • C++
  • ROS (Robot Operating System)
  • PyTorch
  • Large Language Models (LLMs)
  • Vision-Language Models (VLMs)

Benefits

Startup Environment

  • Freedom to implement own ideas
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