Papers
8
Total Citations
55
H-Index
5
About
Omar Lengerke is a robotics researcher whose work bridges industrial automation, intelligent control, and safety-critical systems. His primary research areas include inverse kinematics for robotic manipulators, motion planning for mobile robots, and the application of chaotic control in autonomous systems. Lengerke’s most cited paper (14 citations) introduces a hybrid solution for inverse kinematics on a seven-degree-of-freedom robotic manipulator, combining Genetic Algorithms with the Piper method to improve speed and accuracy—a contribution with direct implications for humanoid robotics and prosthetic design. He has also made notable advances in flexible manufacturing, developing path-planning algorithms for Automated Guided Vehicles (AGVs) that enhance efficiency in modern production lines. In a creative twist, Lengerke has explored chaotic behavior in fire-fighting robots, proposing non-deterministic control strategies to improve surveillance and hazard response in unpredictable environments. His work on differential flatness for trajectory tracking further demonstrates his versatility in both manipulator and mobile robot control. With a career spanning over a decade, Lengerke’s research continues to influence practical robotics, from factory floors to emergency response scenarios.
Research Focus
Key Achievements
Top Papers
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- 3Implementation of Chaotic Behavior on a Fire Fighting Robot9 citations · 2011
- 4Motion planning on Mobile Robots using Differential Flatness8 citations · 2011
- 5Comparative study for chaotic behaviour in fire fighting robot6 citations · 2012
- 6Trajectory tracking for robot manipulators using differential flatness5 citations · 2011
- 7DISEÑO MECATRÓNICO DE UN ROBOT TIPO AGV "AUTOMATED GUIDED VEHICLE"2 citations · 2010
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