Norbert Druml

About

Norbert Druml is a researcher specializing in sensor fusion, time-of-flight (ToF) imaging, and autonomous perception systems, with a particular focus on advancing environment sensing for automotive and robotic applications. His most recognized contribution is the development of an open hardware and software framework for fusing heterogeneous sensor data — notably radar and ToF sensors — enabling researchers to efficiently design and benchmark low-level fusion strategies without information loss during preprocessing. This foundational work has garnered 15 citations and laid the groundwork for subsequent studies in occupancy grid fusion and context-aware sensor adaptation. Druml's research consistently addresses real-world challenges in autonomous systems, including indoor positioning, mixed-criticality safety architectures, and the impact of adverse atmospheric conditions such as fog on ToF imaging accuracy. His investigation into fog-induced sensor perturbations using ray-tracing simulations reflects a commitment to robust, deployment-ready perception systems. He has also advanced multi-sensor synchronization through hybrid timestamping approaches, critical for reliable low-level data fusion. With a cumulative citation count exceeding 60 across his top publications, Druml's work represents meaningful progress in bridging sensor hardware capabilities with intelligent, safety-conscious perception pipelines — making him a valuable reference for students and engineers working on autonomous vehicles and industrial robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Design of a Low-Level Radar and Time-of-Flight Sensor Fusion Framework

   15 citations · 2018
2. 2
   Occupancy Grid Fusion of Low-Level Radar and Time-of-Flight Sensor Data

   11 citations · 2019
3. 3
   High-performance indoor positioning and pose estimation with time-of-flight 3D imaging

   10 citations · 2017
4. 4
   A 3D Time-of-Flight Mixed-Criticality System for Environment Perception

   8 citations · 2017
5. 5
   Hybrid Sensing Approach For Coded Modulation Time-of-Flight Cameras

   7 citations · 2019
6. 6
   Fog Effects on Time-of-Flight Imaging Investigated by Ray-Tracing Simulations

   4 citations · 2018
7. 7
   A Hybrid Timestamping Approach for Multi-Sensor Perception Systems

   3 citations · 2020
8. 8
   Context-Aware Sensor Adaption of a Radar and Time-of-Flight Based Perception Platform

   2 citations · 2020

Key Collaborators

Contact & Links