Papers
4
Total Citations
17
H-Index
2
About
Ercan Elibol is a robotics researcher dedicated to making humanoid robots more energy-efficient and environmentally sustainable. His primary research areas focus on power-aware motion planning and control for humanoid locomotion, particularly in optimizing energy usage during critical tasks like walking, standing up, and sitting down. Elibol’s most influential work, "Optimizing Energy Usage through Variable Joint Stiffness Control during Humanoid Robot Walking" (2014, 7 citations), introduced a novel approach to dynamically adjust joint stiffness, significantly reducing power consumption without compromising stability. He further advanced this field by analyzing electrical and mechanical power flows during sit-stand transitions (2016, 6 citations), providing a foundational framework for understanding motor dynamics in humanoid tasks. Demonstrating innovation in machine learning, Elibol applied Q-learning to minimize power usage during standing processes (2015, 2 citations), showcasing how reinforcement learning can optimize joint trajectories. Notably, his later work on "Toward Upcycled and Sustainable Robotics" (2019, 2 citations) reflects a forward-thinking shift toward accessible, flexible, and environmentally friendly robotic platforms using repurposed components. With a total of 17 citations across his key papers, Elibol’s contributions are steadily influencing both energy-efficient humanoid control and sustainable robotics design.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Power Usage Reduction of Humanoid Standing Process Using Q-Learning2 citations · 2015
- 4