Papers
29
Total Citations
297
H-Index
9
About
Dianxi Shi is a robotics and computer vision researcher whose work spans autonomous navigation, multi-robot systems, and bio-inspired sensing technologies. His research has made significant contributions to the fields of event-based perception, visual-inertial odometry, and coverage path planning — areas critical to the advancement of intelligent autonomous systems. Shi's most notable contributions include FA-Harris (2019, 56 citations), a pioneering fast and asynchronous corner detection method for event cameras, and PLC-VIO (2021, 38 citations), a tightly coupled visual-inertial odometry system leveraging point-line constraints for robust robot localization. His 2023 work on ESVIO extended event-based sensing to stereo configurations, while his research on multi-robot Dubins coverage path planning (2023, 44 citations) addressed complex real-world challenges in aerial monitoring and search-and-rescue operations. Beyond perception, Shi has explored cloud-based UAV control architectures, multi-robot formation control using the Hungarian method, and dynamic task allocation strategies, demonstrating a breadth that bridges theoretical algorithms and practical deployment. With over 230 cumulative citations across a decade of research, his work reflects a sustained and growing influence on the robotics community, particularly in enabling autonomous robots to perceive and navigate complex dynamic environments more effectively.
Research Focus
Key Achievements
Top Papers
- 1FA-Harris: A Fast and Asynchronous Corner Detector for Event Cameras56 citations · 2019
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- 3PLC-VIO: Visual–Inertial Odometry Based on Point-Line Constraints38 citations · 2021
- 4ESVIO: Event-Based Stereo Visual-Inertial Odometry22 citations · 2023
- 5A Cloud-based Control System Architecture for Multi-UAV19 citations · 2018
- 6A Review of Indoor-Outdoor Scene Classification14 citations · 2017
- 7Complete coverage problem of multiple robots with different velocities11 citations · 2022
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