Martin Lauer

About

Martin Lauer is a leading researcher in autonomous systems, with core expertise spanning robot self-localization, 3D urban scene understanding, and cooperative motion planning for automated vehicles. His most influential work, "Calculating the Perfect Match" (2006, 101 citations), introduced an efficient and accurate approach for robot self-localization that remains foundational in the field. Lauer made significant contributions to 3D scene understanding from movable platforms (57 citations), developing generative models that bridge the gap between basic segmentation and the high accuracy required for autonomous driving. He also pioneered cooperative motion planning through the CoInCar-Sim simulation framework (40 citations), enabling research into how automated vehicles can interact and coordinate. His work extends to practical perception challenges, including stair detection using stereo vision (32 citations) for robots navigating complex environments, and real-time 3D ball recognition for RoboCup applications (27 citations). More recently, Lauer has advanced decision-making for automated vehicles using hierarchical behavior-based arbitration (27 citations) and developed reinforcement learning approaches for path tracking that transfer from simulation to real car-like robots (22 citations). His research consistently addresses the gap between theoretical algorithms and real-world robotic deployment.

Research Focus

Key Achievements

Top Papers

1. 1
   Calculating the Perfect Match: An Efficient and Accurate Approach for Robot Self-localization

   101 citations · 2006
2. 2
   A generative model for 3D urban scene understanding from movable platforms

   57 citations · 2011
3. 3
   CoInCar-Sim: An Open-Source Simulation Framework for Cooperatively Interacting Automobiles

   40 citations · 2018
4. 4
   Detection of ascending stairs using stereo vision

   32 citations · 2015
5. 5
   Decision-Making for Automated Vehicles Using a Hierarchical Behavior-Based Arbitration Scheme

   27 citations · 2020
6. 6
   Real-time 3D Ball Recognition using Perspective and Catadioptric Cameras.

   27 citations · 2007
7. 7
   Learning Path Tracking for Real Car-like Mobile Robots From Simulation

   22 citations · 2019
8. 8
   Modeling Moving Objects in a Dynamically Changing Robot Application

   18 citations · 2005
9. 9
   Making a Robot Learn to Play Soccer Using Reward and Punishment

   16 citations · 2007
10. 10
    Sampling-based Inverse Reinforcement Learning Algorithms with Safety Constraints

    14 citations · 2021

Key Collaborators

Contact & Links