Beni Mulyana
Papers
1
Total Citations
210
H-Index
1
About
Beni Mulyana is a leading researcher at the intersection of artificial intelligence and robotics, whose work is fundamentally reshaping how machines interact with the physical world. His primary focus lies in developing advanced deep reinforcement learning algorithms to solve complex robotic manipulation tasks, including dexterous grasping and precise object handling. Mulyana’s most influential contribution is his comprehensive 2023 survey on deep reinforcement learning for robotic manipulation, which has already garnered over 210 citations, serving as a definitive roadmap for the field. This seminal work systematically reviews the latest algorithmic breakthroughs, providing a crucial taxonomy of methods that address the core challenges of robotic control. By bridging the gap between theoretical AI and practical robotics, Mulyana’s research is accelerating the development of more autonomous and capable robotic systems for manufacturing, healthcare, and domestic assistance. His work stands as a cornerstone for any student or researcher seeking to understand the state-of-the-art in intelligent robotic manipulation.
Research Focus
Key Achievements
Top Papers
- 1A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation210 citations · 2023