Papers
1
Total Citations
15
H-Index
1
About
Jonas Mohrs is an emerging researcher specializing in embedded computer vision, real-time image processing, and unmanned aerial vehicle (UAV) systems. His work sits at the intersection of robotics, parallel computing, and stereo vision, addressing the growing demand for high-performance yet resource-constrained processing solutions in modern autonomous systems. Mohrs is best known for his 2021 contribution, "ReS2tAC," which presents a UAV-borne real-time stereo matching system optimized for embedded ARM and CUDA devices. This work tackled a longstanding challenge in the field: enabling computationally intensive Semi-Global Matching (SGM) stereo algorithms to run efficiently on lightweight embedded hardware, moving beyond traditional FPGA-dependent approaches. By leveraging modern GPU architectures available on embedded platforms, his research democratized high-performance stereo vision for low-cost robotic systems, making sophisticated depth perception more accessible for aerial robotics applications. With 15 citations, his work has gained meaningful traction within the embedded vision and UAV research communities. For students and researchers working on autonomous navigation, drone-based mapping, or real-time 3D reconstruction, Mohrs' contributions offer valuable insights into practical, scalable solutions for deploying advanced stereo vision algorithms in resource-limited environments.
Research Focus
Key Achievements
Top Papers
- 1