Papers
13
Total Citations
1,531
H-Index
8
About
Mihail Pivtoraiko is a leading researcher in autonomous robotics, specializing in motion planning, kinodynamic optimization, and model-predictive control. His most influential contribution is the development of CHOMP (Covariant Hamiltonian Optimization for Motion Planning), a groundbreaking trajectory optimization method that uses functional gradient techniques to iteratively refine robot paths. With 738 citations, this work has become a cornerstone of modern motion planning, enabling robots to navigate complex environments efficiently. Pivtoraiko also pioneered the use of state lattice motion primitives for differentially constrained robots, as detailed in his highly cited 2009 paper (380 citations), which introduced deterministic search in discretized state spaces to guarantee constraint satisfaction. His research extends to integrated manipulation systems, where he combined perception, planning, and control for autonomous grasping (120 citations). Notable achievements include advancing kinodynamic planning with pre-computed motion primitives and developing graduated fidelity replanning strategies. With over 1,500 total citations, Pivtoraiko’s work has profoundly impacted autonomous navigation, manipulation, and real-world robotics applications, making him a key figure in the field.
Research Focus
Key Achievements
Top Papers
- 1CHOMP: Covariant Hamiltonian optimization for motion planning738 citations · 2013
- 2Differentially constrained mobile robot motion planning in state lattices380 citations · 2009
- 3An integrated system for autonomous robotics manipulation120 citations · 2012
- 4Kinodynamic motion planning with state lattice motion primitives107 citations · 2011
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- 7Autonomous robot navigation using advanced motion primitives17 citations · 2009
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- 9Path Set Relaxation for Mobile Robot Navigation6 citations · 2010
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