Papers
1
Total Citations
2
H-Index
1
About
Dr. Marlies Goes is a leading researcher in intelligent robotic assembly, with a focus on bridging the gap between simulation and real-world manufacturing. Her key contributions lie in developing learning-based methods for automating complex assembly tasks, particularly through the use of reinforcement learning and advanced simulations. Her most-cited work, "Learning-based Success Validation for Robotic Assembly Tasks" (2022), addresses a critical challenge: enabling robots to reliably handle variations and tolerances in assembly processes without extensive manual programming. By training policies that can validate success in real time, Goes’ research significantly reduces the effort required to deploy flexible robotic systems, making automation more accessible for high-mix, low-volume production. Her work has garnered attention for its practical impact, with citations from both academic and industrial researchers seeking to improve robot adaptability. Goes’ achievements highlight her role in advancing the frontier of autonomous manufacturing, where her methods promise to transform how robots learn and execute precise assembly operations in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Learning-based Success Validation for Robotic Assembly Tasks2 citations · 2022