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About

Heiko Mosemann is a robotics researcher whose work has made significant contributions to the field of automated assembly planning and robot manipulation. His research focuses on three interconnected areas: assembly sequence planning, skill primitive decomposition, and contact state recognition for force-guided assembly operations. Mosemann's most influential contribution, "Automatic decomposition of planned assembly sequences into skill primitives" (2001, 87 citations), introduced a groundbreaking method for breaking down complex assembly operations using AND/OR graph analysis — a technique that has become widely referenced in robotic automation literature. This work fundamentally advanced how robots interpret and execute assembly tasks. His complementary research on regrasp planning (2003, 34 citations) addressed a critical limitation in industrial robotic systems, enabling more flexible and autonomous pick-and-place operations. Throughout the late 1990s and early 2000s, Mosemann consistently tackled the challenge of generating physically stable and geometrically valid assembly sequences, incorporating constraints related to cost efficiency, stability evaluation, and real-world uncertainty. His investigations into contact state classification using polyhedral convex cones further refined how robots handle the inevitable positional uncertainties during execution. With over 150 cumulative citations, his body of work represents a cohesive and practically grounded contribution to intelligent manufacturing robotics.