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About

Mahyar Abdeetedal’s research lies at the intersection of robotic manipulation, grasp synthesis, and purposeful object interaction—a field where robots are taught not just to hold objects, but to break them with precision. His most influential work, “Grasp synthesis for purposeful fracturing of object” (13 citations), pioneers a novel approach to robotic grasping: designing grasps that intentionally fail or yield an object, such as snapping a crop stem during harvesting. This work is complemented by his development of an open-source integration platform for Kuka robots (12 citations), which lowers barriers for researchers working with modular peripheral systems. Abdeetedal’s contributions extend to whole-limb manipulation, where he introduced an optimal adaptive Jacobian internal forces controller that handles kinematic uncertainties in multi-limb robots (7 citations). His earlier, scale-dependent method for whole arm grasp evaluation (3 citations) introduced the concept of “size ratio,” addressing the underexplored challenge of manipulating objects comparable to the robot’s own size. Through his focus on applying controlled internal forces and shear stresses to induce beam failure, Abdeetedal has carved a niche in robotic harvesting and industrial fracturing, offering practical solutions that bridge grasp theory and real-world application.