Jeffrey Uhlmann

About

Jeffrey Uhlmann is a pioneering researcher in mobile robotics and applied linear algebra, best known for foundational contributions to simultaneous localization and mapping (SLAM) and the development of a unit-consistent generalized matrix inverse. His early work on multi-robot systems operating in large environments—such as the landmark paper “Building a million beacon map” (2001, 23 citations)—addressed the critical challenge of robot localization without GPS, enabling long-duration autonomous missions in GPS-denied settings like city streets. Uhlmann also advanced the theory of matrix inverses with his 2018 paper introducing a generalized inverse consistent with diagonal transformations (22 citations), solving a longstanding open problem with broad implications for state-space control and robotic systems. His subsequent work applying this inverse to stable robotic control (2019, 7 citations) demonstrates its practical impact on reducing sensitivity to coordinate frame choices. With additional contributions to real-time distributed map building and multi-SLAM algorithm evaluation, Uhlmann’s research bridges theoretical rigor and real-world deployment, earning him recognition as a key figure in scalable, robust autonomous navigation.

Research Focus

Key Achievements

Top Papers

1. 1
   <title>Building a million beacon map</title>

   23 citations · 2001
2. 2
   A Generalized Matrix Inverse That Is Consistent with Respect to Diagonal Transformations

   22 citations · 2018
3. 3
   Using multiple slam algorithms

   9 citations · 2004
4. 4
   Applying a Unit-Consistent Generalized Matrix Inverse for Stable Control of Robotic Systems

   7 citations · 2019
5. 5
   <title>Real-time distributed map building in large environments</title>

   7 citations · 2000
6. 6
   A Generalized Matrix Inverse with Applications to Robotic Systems

   5 citations · 2018

Key Collaborators

Contact & Links