Jorge Molina

Papers

Total Citations

100

H-Index

About

Jorge Molina’s research lies at the intersection of robotics, artificial intelligence, and industrial automation, with a focus on developing intelligent systems for complex real-world tasks. His most impactful work, “Pick and Place Operations in Logistics Using a Mobile Manipulator Controlled with Deep Reinforcement Learning” (81 citations), pioneers the use of deep reinforcement learning to enable robots to autonomously perform intricate logistics operations—reducing the need for expensive, manually programmed path planning. This contribution has significant implications for warehouse and supply chain automation. Molina also advanced inspection robotics through his work on thermal tracking for leak detection in solar thermal plants (17 citations) and non-destructive inspection of industrial equipment via the MAINBOT project. These efforts demonstrate his commitment to deploying mobile manipulators—both ground and climbing robots—for autonomous maintenance in challenging environments. Molina’s research is notable for bridging the gap between cutting-edge AI control methods and practical industrial applications, offering scalable solutions for efficiency and safety. His work continues to influence the fields of service robotics and intelligent manufacturing.