Alexander Pekarovskiy
Institute for Advanced Study, Technical University of Munich
Papers
6
Total Citations
73
H-Index
5
About
Alexander Pekarovskiy is a roboticist specializing in dynamic manipulation and real-time motion generation for robotic systems. His research focuses on enabling robots to perform complex, high-speed tasks like throwing, catching, and juggling with nonprehensile end-effectors—manipulators that cannot simply grasp objects. Pekarovskiy’s major contributions include developing a spline-based trajectory deformation method that allows robots to adapt fast motions online in response to changing conditions, as detailed in his most-cited work (25 citations). He also pioneered an optimal control approach for planar nonprehensile throwing (13 citations) and introduced a robust trajectory design that minimizes landing uncertainty despite model errors (11 citations). His work on online deformation of optimal trajectories (10 citations) and hierarchical robustness for catching (9 citations) further advances the field. Notably, Pekarovskiy explored resonance-driven dynamic manipulation, using an elastic beam end-effector to dribble and juggle objects (5 citations), demonstrating energy-efficient, repetitive task execution. With over 70 total citations, his research bridges motion planning, control theory, and real-world robotics, offering practical solutions for autonomous systems in unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Optimal control goal manifolds for planar nonprehensile throwing13 citations · 2013
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