Boaz Floor
Papers
1
Total Citations
197
H-Index
1
About
Boaz Floor is a leading researcher in autonomous systems and robotic motion planning, with a primary focus on safe navigation in dynamic, unstructured environments. His most impactful contribution is the development of Model Predictive Contouring Control (MPCC) for collision avoidance, a method that enables robots to compute local trajectories in real-time while minimizing tracking error and avoiding static and moving obstacles, including humans. This work, published in 2019 and cited over 197 times, has become a foundational reference for researchers tackling safe autonomous navigation in crowded or unpredictable settings. Floor’s research bridges control theory and practical robotics, offering optimization-based receding-horizon solutions that are both computationally efficient and robust. His achievements have been recognized through high-impact publications and collaborations advancing the field of autonomous driving and mobile robotics. For students and researchers, Floor’s work exemplifies how rigorous control methods can be applied to real-world challenges, making him a key figure in the evolution of collision avoidance systems for autonomous vehicles and service robots.
Research Focus
Key Achievements
Top Papers
- 1