Papers
10
Total Citations
298
H-Index
7
About
Nuwan Ganganath’s research centers on energy-efficient mobile robot navigation, path planning on uneven terrains, and optimization algorithms for autonomous systems. His major contributions include developing the Z* search algorithm and its dynamic variants for rapid replanning of energy-efficient paths, addressing the critical challenge that shortest paths often fail to minimize energy consumption or satisfy climbing constraints on irregular ground. His work integrates heuristic and ant colony optimization (ACO) approaches to produce constraint-aware, multiobjective path planners, and he has also advanced trajectory planning for 3D printing by reframing it as a traveling salesman problem. With over 298 total citations across his top ten papers, his most cited work—"A Constraint-Aware Heuristic Path Planner for Finding Energy-Efficient Paths on Uneven Terrains" (97 citations)—and "Mobile robot localization using odometry and kinect sensor" (87 citations) highlight his impact in both theoretical and practical robotics. Ganganath’s innovations enable longer autonomous operations in hostile outdoor environments, making his research vital for field robotics, search-and-rescue, and sustainable automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Mobile robot localization using odometry and kinect sensor87 citations · 2012
- 3Trajectory planning for 3D printing: A revisit to traveling salesman problem39 citations · 2016
- 4Finding energy-efficient paths on uneven terrains16 citations · 2014
- 5A 2-Dimensional ACO-Based Path Planner for Off-Line Robot Path Planning16 citations · 2013
- 6An ACO-based off-line path planner for nonholonomic mobile robots15 citations · 2014
- 7Multiobjective path planning on uneven terrains based on NAMOA10 citations · 2016
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