Jingru Luo
Papers
7
Total Citations
158
H-Index
7
About
Jingru Luo is a roboticist whose research focuses on whole-body motion planning, robust trajectory optimization, and multi-limbed locomotion for humanoid robots, particularly in complex, contact-rich environments. Her most significant contributions center on enabling humanoid robots to climb ladders and navigate industrial structures—a critical capability for disaster response and maintenance tasks. Luo’s work on the DARPA Robotics Challenge (DRC) stands out, where she developed autonomous planning and control frameworks for the DRC-Hubo robot to climb general ladder- and stair-like structures, as detailed in her highly cited 2014 paper (33 citations). She also pioneered robust trajectory optimization methods under frictional contact using iterative learning, addressing the challenge of modeling errors that cause constraint violations on real robots (39 citations). Her earlier work introduced a novel method for generating dynamically feasible robot trajectories from freehand sketches, making robot programming more intuitive. With over 158 total citations across her key papers, Luo’s research has advanced the practical deployment of humanoid robots in unstructured, real-world settings, laying the groundwork for safer and more reliable autonomous systems in hazardous environments.
Research Focus
Key Achievements
Top Papers
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- 4Motion planning of ladder climbing for humanoid robots20 citations · 2013
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- 7Unbiased, scalable sampling of closed kinematic chains12 citations · 2013