Iyad Hashlamon
Papers
9
Total Citations
67
H-Index
5
About
Iyad Hashlamon’s research focuses on the control, estimation, and fault tolerance of robotic systems, with a particular emphasis on walking bipeds and high-speed delta robots. His major contributions lie in developing virtual sensor frameworks that enable robots to detect and recover from sensor faults—such as joint, ground reaction force, and slip sensors—without requiring physical redundancy. For instance, his work on the Virtual Joint Sensor (VJS) and Virtual Force Sensor (VFS) allows legged robots to maintain balance and stability even when key sensors fail, addressing a critical challenge in real-world deployment. His most cited paper, “Center of mass states and disturbance estimation for a walking biped” (20 citations), provides a foundational method for online balance assessment under uncertain dynamics. Hashlamon’s impact is demonstrated across a body of work that has accumulated over 65 citations, with applications ranging from bipedal locomotion to industrial delta robots. Notably, his recent research extends these principles to vision-based control and adaptive motion control for high-speed automation, showcasing a versatile approach to robotics that bridges theoretical estimation techniques with practical, real-time performance.
Research Focus
Key Achievements
Top Papers
- 1Center of mass states and disturbance estimation for a walking biped20 citations · 2013
- 2
- 3Experimental verification of an orientation estimation technique for autonomous robotic platforms8 citations · 2010
- 4
- 5
- 6A novel method for slip prediction of walking biped robots5 citations · 2015
- 7Real-time vision-based controller for delta robots4 citations · 2021
- 8Simple Virtual Slip Force Sensor for walking biped robots3 citations · 2013
- 9