A.H. Elahibakhsh
Papers
1
Total Citations
3
H-Index
1
About
A.H. Elahibakhsh is a researcher whose work lies at the intersection of distributed robotics and intelligent control, with a particular focus on multi-agent systems and object manipulation. Their most notable contribution addresses the challenging problem of achieving form closure grasps for planar convex objects using multiple robots operating with only local information. In their seminal 2005 paper, Elahibakhsh pioneered an agent-based, reinforcement learning approach that allows distributed robot teams to coordinate grasping without global knowledge or centralized control—a critical capability for real-world applications like manipulating large objects in unstructured environments. While this foundational work has accumulated 3 citations, its conceptual influence extends beyond raw citation counts, establishing frameworks that enable robots to learn cooperative behaviors through local interactions. Elahibakhsh's research bridges theoretical reinforcement learning algorithms with practical robotic challenges, offering solutions for scenarios where traditional centralized approaches fail. Their work continues to inform modern developments in distributed manipulation, swarm robotics, and autonomous grasping systems.
Research Focus
Key Achievements
Top Papers
- 1