Jacqueline Libby
Carnegie Mellon University, Stevens Institute of Technology, New York University
Papers
9
Total Citations
253
H-Index
7
About
Jacqueline Libby is a robotics researcher whose work spans autonomous manipulation, agricultural robotics, neurorobotics, and soft robotics. Her most cited paper, "An integrated system for autonomous robotics manipulation" (2012, 120 citations), established a framework for dexterous object grasping through tight integration of perception, planning, and control. She made significant contributions to GPS-free localization for specialty agriculture, developing perception-based systems using laser rangefinders and extended Kalman filters that achieve sub-meter accuracy in orchards, as detailed in her 2011 and 2010 papers (39 and 9 citations respectively). Libby also pioneered multimodal terrain classification, using sound and vibration from robot-terrain interaction to improve offroad perception (40 citations). More recently, she has advanced neurorobotics with deep learning architectures like heterogeneous dilation LSTM for transient-phase gesture prediction from high-density electromyography (2022, 24 citations), and explored evolutionary algorithm optimization for PID controllers in pneumatic soft robotic systems (2024, 8 citations). Her work on soft actuator fatigue (2023, 8 citations) addresses durability challenges in rehabilitative robotics. With over 250 total citations, Libby's research demonstrates a consistent focus on integrating perception, control, and learning across diverse robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1An integrated system for autonomous robotics manipulation120 citations · 2012
- 2Using sound to classify vehicle-terrain interactions in outdoor environments40 citations · 2012
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- 7What Happens When Pneu-Net Soft Robotic Actuators Get Fatigued?8 citations · 2023
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