Gorkem Erinc
Constructor University, AmeriCorps, University of California, Merced
Papers
10
Total Citations
104
H-Index
5
About
Gorkem Erinc’s research lies at the intersection of mobile robotics, multi-robot systems, and autonomous navigation, with a particular focus on enabling heterogeneous robot teams to operate effectively in unknown environments. His major contributions center on solving the challenges of nonholonomic motion planning, WiFi-based localization, and appearance-based map merging. His most cited work, "A genetic algorithm for nonholonomic motion planning" (2007, 27 citations), introduces an evolutionary approach to generating and optimizing feasible paths for robots with motion constraints. Erinc has also pioneered methods for real-time WiFi localization of heterogeneous robot teams using online random forests (2015, 24 citations), allowing robots to map and localize without prior knowledge of access point locations. His work on anytime merging of appearance-based maps (2013, 15 citations) enables multiple robots to collaboratively build and share spatial representations using visual features like SIFT descriptors. Through these contributions, Erinc has advanced the practical deployment of multi-robot systems in GPS-denied indoor environments, demonstrating how heterogeneous platforms can cooperate to achieve situational awareness and robust navigation.
Research Focus
Key Achievements
Top Papers
- 1A genetic algorithm for nonholonomic motion planning27 citations · 2007
- 2
- 3Anytime merging of appearance-based maps15 citations · 2013
- 4
- 5Image-based mapping and navigation with heterogenous robots7 citations · 2009
- 6Anytime merging of appearance based maps5 citations · 2012
- 7
- 8
- 9Heterogeneous map merging using WiFi signals3 citations · 2013
- 10Evaluation criteria for appearance based maps2 citations · 2010