Megumu Koike
Papers
2
Total Citations
30
H-Index
2
About
Megumu Koike is a robotics researcher whose work focuses on the critical challenge of autonomous navigation for non-holonomic mobile robots, particularly in constrained agricultural environments. Koike’s primary research areas include path planning, mapping, and sensor selection for car-like robots that face kinematic constraints in narrow pathways. Their most impactful contribution, the 2021 paper "Evaluation of mapping and path planning for non-holonomic mobile robot navigation in narrow pathway for agricultural application," has garnered 28 citations, establishing it as a key reference in the field. This work systematically evaluates the trade-offs between depth cameras and LiDAR sensors, addressing the complex balance of cost, robustness, and data processing for real-world agricultural applications. Koike also advanced the field with their 2020 analysis of the RRT* algorithm integrated with Reeds-Shepp curves, specifically tackling the difficult problem of forward-only motion planning in tight spaces. By bridging theoretical path planning with practical sensor implementation, Koike’s research provides essential guidance for developing cost-effective, reliable autonomous systems in agriculture, making their work valuable for students and researchers working on field robotics and precision agriculture.
Research Focus
Key Achievements
Top Papers
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