D. Burschkal
Papers
1
Total Citations
41
H-Index
1
About
D. Burschkal is a researcher in mobile robotics and computer vision, with a focus on stereo-based perception for autonomous navigation. Their most cited work, "Stereo-based obstacle avoidance in indoor environments with active sensor re-calibration" (2003, 41 citations), introduces a robust system that models and removes the supporting surface from stereo data, then segments remaining disparities to identify obstacles. This contribution addresses a critical challenge in robotics: enabling vehicles to navigate cluttered indoor spaces without prior mapping. By incorporating active sensor re-calibration, Burschkal’s approach enhances reliability in dynamic environments, a key step toward practical autonomous systems. While their citation count reflects a specialized impact, the work is foundational for researchers in obstacle detection and real-time stereo vision. Burschkal’s methodology—combining geometric modeling with segmentation—has influenced subsequent studies in safe navigation for mobile robots, demonstrating a lasting contribution to the field.
Research Focus
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Top Papers
- 1