Markus Lieret
Papers
4
Total Citations
38
H-Index
3
About
Markus Lieret is a robotics researcher whose work spans industrial automation, autonomous systems, and assistive robotics. His most cited paper, "6DoF Pose-Estimation Pipeline for Texture-less Industrial Components in Bin Picking Applications" (2019, 23 citations), addresses a critical challenge in manufacturing: enabling robots to accurately recognize and grasp untextured parts in cluttered bins. This work has direct implications for automating shop floors and reducing reliance on manual labor. Lieret also contributes to safety in aerial robotics, proposing a redundant flight control architecture for fault detection in multirotor UAVs (2020, 9 citations), a key step toward reliable drone delivery systems. In assistive technology, his multimodal A* algorithm (2023, 4 citations) optimizes how intelligent wheelchairs accompany users, blending path planning with human-aware navigation. Additionally, his research on RGB-D-based human detection and segmentation (2021, 2 citations) supports safe mobile robot navigation in industrial environments. With a focus on perception, pose estimation, and fault tolerance, Lieret’s work bridges the gap between theoretical robotics and real-world deployment, making autonomous systems more capable, safer, and more accessible across industries.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4