Papers
2
Total Citations
9
H-Index
2
About
Eli Lancaster is a field robotics researcher whose work centers on enabling autonomous mobile robots to navigate challenging, off-road environments with greater safety and efficiency. His primary research areas include kinodynamic motion planning, terrain-aware navigation, and adaptive testing methodologies for field robotics. Lancaster’s major contribution is the development of terrain-aware kinodynamic planners that explicitly account for non-flat terrain—using elevation maps and vehicle suspension models to estimate roll and pitch—allowing robots to plan safer, more efficient paths across uneven ground. His most cited work, “Terrain-Aware Kinodynamic Planning with Efficiently Adaptive State Lattices for Mobile Robot Navigation in Off-Road Environments” (2023, 6 citations), introduces an adaptive state lattice approach that balances computational efficiency with terrain responsiveness. In a complementary study on active learning for testing and evaluation (2022, 3 citations), Lancaster argues for adaptive, human-supervised experimentation to better assess robotic systems under real-world conditions. Though early in his career, his work is already shaping how autonomous ground vehicles perceive and move through complex, unstructured landscapes—a critical step toward deploying robots in agriculture, search-and-rescue, and planetary exploration.
Research Focus
Key Achievements
Top Papers
- 1
- 2