Papers
1
Total Citations
4
H-Index
1
About
Kaiqi Ren is a robotics researcher whose work focuses on the critical challenge of autonomous navigation in extreme environments. His primary research areas include motion planning, sensor integration, and control systems for mobile robots operating in underground and confined spaces. Ren’s most notable contribution is his 2022 paper, "Evaluation of Motion Planning Algorithms for Underground Mobile Robots," which systematically assesses the performance of various path-planning algorithms in GPS-denied, low-visibility subterranean settings. This work provides a foundational benchmark for developing more robust and reliable autonomous systems for mining, search-and-rescue, and infrastructure inspection. While his citation count is still growing—with 4 citations to date—his research addresses a pressing need in field robotics, where safety and efficiency are paramount. Ren’s work is particularly relevant for students and engineers interested in the intersection of algorithm design and real-world deployment, offering practical insights into the trade-offs between computational efficiency and navigational accuracy in challenging terrains.
Research Focus
Key Achievements
Top Papers
- 1Evaluation of Motion Planning Algorithms for Underground Mobile Robots4 citations · 2022