Papers
9
Total Citations
91
H-Index
5
About
Alexander Kurdas is a leading researcher in the field of physical human-robot interaction (pHRI), with a primary focus on safety benchmarking, collision dynamics, and impact-aware manipulation. His work addresses the critical challenge of enabling robots to work safely and efficiently alongside humans in shared, collaborative workspaces. Kurdas has made major contributions by developing novel frameworks for quantifying and mitigating robot collision risks. Notably, he introduced the concept of "Mean Reflected Mass" as a physically interpretable metric for safety assessment and posture optimization, and pioneered the "Modularize-and-Conquer" framework for safe precollision control of floating-base robots. His research also advances online payload identification using momentum observers and functional mode switching for adaptive safety during tasks. With over 90 citations across his most-cited works, Kurdas has helped establish standardized performance measurement protocols for tactile robots, bridging the gap between experimental injury biomechanics and robotic control. His work on distinguishing between expected and unexpected post-impact behaviors is foundational for the emerging field of impact-aware manipulation, where intentional collisions are exploited to improve robotic efficiency.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Online Payload Identification for Tactile Robots Using the Momentum Observer16 citations · 2022
- 4
- 5Real-time IMU-Based Learning: a Classification of Contact Materials7 citations · 2022
- 6Functional Mode Switching for Safe and Efficient Human-Robot Interaction5 citations · 2022
- 7
- 8
- 9Global Safety Characteristics of Wheeled Mobile Manipulators3 citations · 2022