Michael Hemmer
Papers
7
Total Citations
73
H-Index
5
About
Michael Hemmer is a computational geometry and robotics researcher whose work spans motion planning, swarm robotics, and combinatorial geometry. He is perhaps best known for his contributions to the Motion Planning via Manifold Samples (MMS) framework, a hybrid algorithmic approach that bridges exact geometric analysis of low-dimensional configuration spaces with sampling-based methods suited for higher dimensions. His investigations into the dimensionality of narrow passages have advanced understanding of how robotic systems can efficiently explore complex configuration spaces, earning his most-cited work 28 citations. Beyond motion planning, Hemmer has made significant contributions to distributed swarm robotics, developing local cohesive control mechanisms that enable robot swarms to maintain connectivity under external forces and node failures — work that has garnered over 20 citations. His research also extends into combinatorial problems, notably the Chromatic Art Gallery Problem, where he analyzed the computational complexity of guard-coloring strategies in polygonal environments. Across these diverse areas, Hemmer demonstrates a consistent ability to unite theoretical rigor with practical algorithmic design, making his work valuable to researchers in robotics, algorithm theory, and computational geometry alike.
Research Focus
Key Achievements
Top Papers
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- 4Motion Planning via Manifold Samples5 citations · 2011
- 5Complexity of the General Chromatic Art Gallery Problem5 citations · 2014
- 6A parallel distributed strategy for arraying a scattered robot swarm2 citations · 2015
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