Michael Cashmore

King's College London, University of Strathclyde

Papers

Total Citations

488

H-Index

About

Michael Cashmore is a leading researcher at the intersection of artificial intelligence, task planning, and robotics, best known for his foundational work on integrating automated planning with the Robot Operating System (ROS). His landmark paper, "ROSPlan: Planning in the Robot Operating System" (2015, 223 citations), introduced a versatile, modular framework that enables robotic systems to reason about actions and achieve high-level goals, becoming a standard tool for the robotics community. This work, alongside his contributions to the IEEE International Conference on Robotics and Automation (ICRA 2014, 252 citations), has profoundly shaped how robots are programmed for complex, goal-directed behavior. Cashmore has also advanced the field of autonomous perception with research on "On-the-fly detection of novel objects in indoor environments," tackling the challenge of efficient, real-time object discovery. More recently, he has explored adaptive control in extreme environments, as seen in his work on "Meta Reinforcement Learning Based Underwater Manipulator Control" (2021), applying cutting-edge machine learning to enable robust manipulation in deep-sea conditions. With over 500 citations across his most influential works, Cashmore’s research continues to bridge the gap between symbolic planning and real-world robotic execution.