Yaqi Jing
Papers
1
Total Citations
7
H-Index
1
About
Yaqi Jing is a researcher specializing in robotics and chemical plume tracing (CPT), with a focus on autonomous navigation in complex, odor-driven environments. Their most-cited work, "Learning to Rapidly Re-Contact the Lost Plume in Chemical Plume Tracing" (2015, 7 citations), addresses a critical challenge in CPT: maintaining continuous contact between a robot and a chemical plume after detection is lost. Jing’s major contribution lies in developing a learning-based approach that biases the robot’s heading relative to the upwind direction during the immediate post-loss phase, enabling faster re-contact with the plume. This work enhances the efficiency of autonomous systems in tasks such as environmental monitoring, search-and-rescue, and hazardous material detection. While Jing’s citation count is modest, the research demonstrates practical impact by improving real-time decision-making in robotic olfaction. Their work is notable for bridging machine learning and sensor-based navigation, offering a foundation for future studies in adaptive plume tracing. Jing’s contributions are particularly valuable for students and researchers exploring bio-inspired robotics and autonomous exploration in dynamic, uncertain environments.
Research Focus
Key Achievements
Top Papers
- 1Learning to Rapidly Re-Contact the Lost Plume in Chemical Plume Tracing7 citations · 2015