Jingjing Li

State Key Laboratory of Industrial Control Technology

Papers

Total Citations

H-Index

About

Jingjing Li is an emerging researcher in the field of autonomous robotics and drone systems, with a particular focus on motion planning and aerial vehicle navigation. Their most notable work challenges conventional assumptions in robotic motion planning by exploring what they term "aggressive collision-inclusive motion planning" — a paradigm-shifting approach that reconceptualizes collisions not merely as failures to be avoided, but as strategic tools that can be leveraged to minimize task duration and energy consumption in constrained environments. This work, published in 2024, has already garnered early citations, signaling growing interest in this unconventional approach to drone autonomy. Li's research addresses a critical gap in narrow-environment navigation, where traditional collision-avoidance-first paradigms often prove insufficient or overly conservative. By demonstrating that strategically managed collisions can improve operational efficiency, their contributions open new frontiers for drone deployment in cluttered, real-world scenarios such as search and rescue, infrastructure inspection, and warehouse automation. Though still in the early stages of building their citation profile, Li's willingness to challenge foundational assumptions in robotics positions them as a thought-provoking voice in the next generation of autonomous systems research.