Papers
20
Total Citations
380
H-Index
11
About
Bernd Finkemeyer is a leading figure in intelligent robotic manipulation, whose work bridges the gap between theoretical control theory and practical industrial applications. His core research focuses on sensor-based robot control, force/position control, and task-level programming. Finkemeyer is best known for developing the concept of *Manipulation Primitives* and *Skill Primitive Nets*, which provide a universal, error-tolerant interface between high-level robot programming and low-level sensor-based motion control. His seminal papers on these topics, including "Executing assembly tasks specified by manipulation primitive nets" and "Error-tolerant execution of complex robot tasks based on skill primitives," have each garnered over 65 citations, establishing a foundational framework for compliant assembly. He has also made significant contributions to practical implementations of Mason’s Task Frame Formalism, making complex hybrid force/velocity control accessible for real-world use. Notably, his work "A manipulator plays Jenga" demonstrated the successful integration of force control, distance control, and real-time distributed systems in a complex, interactive task. With a total of over 300 citations across his most influential works, Finkemeyer’s research has been instrumental in advancing the reliability and safety of industrial robots, paving the way for modern human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Executing assembly tasks specified by manipulation primitive nets67 citations · 2005
- 2Error-tolerant execution of complex robot tasks based on skill primitives67 citations · 2004
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- 5A manipulator plays Jenga25 citations · 2008
- 6MiRPA: Middleware for robotic and process control applications20 citations · 2007
- 7A task frame formalism for practical implementations19 citations · 2004
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- 9Towards safe human-robot collaboration15 citations · 2017
- 10Simple two degree of freedom structures and their properties12 citations · 2006