Papers
6
Total Citations
62
H-Index
3
About
Asep Nugroho is a researcher whose work sits at the intersection of energy systems, robotics, and intelligent control. His primary contributions lie in developing advanced algorithms for battery management and state estimation, particularly for lithium-ion batteries. His most cited work, "RLS with optimum multiple adaptive forgetting factors for SoC and SoH estimation of Li-Ion battery" (2017, 21 citations), introduces a novel recursive least square approach that significantly improves the accuracy of state-of-charge and state-of-health predictions—critical for electric vehicles and renewable energy storage. Beyond batteries, Nugroho has made notable strides in autonomous systems. His 2020 paper on "Landing Area Recognition using Deep Learning for Unmanned Aerial Vehicles" (20 citations) addresses a key safety challenge for UAVs in civilian airspace. He also tackles energy sustainability in robotics, proposing intelligent energy management systems that integrate solar harvesting with battery-supercapacitor hybrids for search-and-rescue robots. With a portfolio spanning control theory, deep learning, and power electronics, Nugroho’s work is highly relevant to the next generation of autonomous, energy-efficient systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Landing Area Recognition using Deep Learning for Unammaned Aerial Vehicles20 citations · 2020
- 3Intelligent Energy Management System for Mobile Robot14 citations · 2022
- 4
- 5Formation Control for Mobile Robot using Fuzzy - PI Controller2 citations · 2020
- 6