Thomas Wiemann

About

Thomas Wiemann is a robotics and computer science researcher whose work centers on 3D mapping, robot navigation, and semantic scene understanding. His most significant contributions lie in developing methods for processing point cloud data to generate actionable environmental representations for autonomous robots. His foundational work on polygonal map generation, beginning with automatic construction of indoor maps from 3D point clouds (2010, 21 citations) and the open-source Las Vegas Reconstruction Toolkit (2012, 18 citations), established key infrastructure for the robotics community. Wiemann's most cited work, a 3D Navigation Mesh system for uneven terrain (2016, 49 citations), demonstrated how triangle mesh environments enriched with connectivity graphs enable safe robot path planning across complex surfaces — an approach he later refined with continuous shortest path vector fields on 3D meshes (2021, 28 citations). Parallel research into semantic mapping — recognizing and localizing furniture from sparse sensor data and grounding symbolic knowledge in spatial databases — further bridges perception and higher-level robot reasoning, attracting over 90 combined citations across those works. His open-source contributions, including ROS-integrated mesh visualization tools, reflect a commitment to making advanced 3D mapping accessible, cementing his influence across both academic research and practical robotic deployments.

Research Focus

Key Achievements

Top Papers

1. 1
   3D Navigation Mesh Generation for Path Planning in Uneven Terrain

   49 citations · 2016
2. 2
   Model-based furniture recognition for building semantic object maps

   40 citations · 2015
3. 3
   Grounding semantic maps in spatial databases

   32 citations · 2018
4. 4
   Continuous Shortest Path Vector Field Navigation on 3D Triangular Meshes for Mobile Robots

   28 citations · 2021
5. 5
   Building semantic object maps from sparse and noisy 3D data

   26 citations · 2013
6. 6
   An Extended Evaluation of Open Source Surface Reconstruction Software for Robotic Applications

   26 citations · 2014
7. 7
   Surface Reconstruction from Arbitrarily Large Point Clouds

   22 citations · 2018
8. 8
   Automatic construction of polygonal maps from point cloud data

   21 citations · 2010
9. 9
   A Toolkit for Automatic Generation of Polygonal Maps - Las Vegas Reconstruction

   18 citations · 2012
10. 10
    Tools for Visualizing, Annotating and Storing Triangle Meshes in ROS and RViz

    16 citations · 2019

Key Collaborators

Contact & Links