Tom Hattendorf
Papers
1
Total Citations
9
H-Index
1
About
Tom Hattendorf is a roboticist whose research focuses on motion planning and obstacle avoidance for robotic manipulators in complex, dynamic environments. His most significant contribution is the development of the Informed Circular Fields framework, which extends the circular field predictions (CFP) planner to enable global reactive obstacle avoidance for the entire structure of a robotic arm. This work, published in 2023, addresses a critical challenge in robotics: ensuring safe, real-time navigation of manipulators through cluttered or unpredictable spaces without relying on precomputed paths. With 9 citations in its first year, the paper has quickly gained attention for its practical implications in industrial automation and human-robot collaboration. Hattendorf’s approach stands out for its ability to combine global planning efficiency with reactive local adjustments, making it suitable for tasks like assembly, pick-and-place, and autonomous operation in shared workspaces. His research bridges the gap between theoretical motion planning and real-world deployment, offering a robust solution for robots that must adapt on the fly. For students and researchers, Hattendorf’s work exemplifies how foundational algorithms can be refined to meet the demands of modern robotics, paving the way for safer, more autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1