Matthias Propst

About

Matthias Propst is a researcher at the forefront of human-robot collaboration (HRC), focusing on making industrial robotics accessible to non-experts. His work centers on developing intuitive, programming-free interfaces and robust skill execution frameworks that enable seamless teamwork between humans and robots in assembly tasks. Propst’s major contributions include pioneering the use of behavior trees for robotic skill execution, as detailed in his 2024 paper (8 citations), which provides a structured yet flexible framework for dynamic task adaptation in industrial settings. He also advanced visual programming with the ROBxTASK RTE platform (4 citations), allowing users to orchestrate workflows across diverse robotic systems using Google Blockly—a significant step toward democratizing robot programming. His most cited work (10 citations) explores programming-free approaches for HRC, highlighting his commitment to reducing complexity. With a growing citation record, Propst’s research is shaping the future of agile, human-centric manufacturing, where adaptability and ease of use are paramount.

Research Focus

Key Achievements

Top Papers

1. 1
   Programming-Free Approaches for Human–Robot Collaboration in Assembly Tasks

   10 citations · 2021
2. 2
   Towards a Behavior Tree Based Robotic Skill Execution Framework for Human Robot Collaboration in Industrial Assembly

   8 citations · 2024
3. 3
   ROBxTASK RTE - a lightweight runtime environment to implement collaborative processes across different robotic systems

   4 citations · 2022
4. 4
   Framework for Reducing the Complexity of Programming Robot Skills

   2 citations · 2023
5. 5
   Dynamic Adaptability in Human-Robot Collaboration for Industrial Assembly: A Behaviour Tree Based Task Execution

   1 citations · 2024

Key Collaborators

Contact & Links