James Rogers
Papers
1
Total Citations
11
H-Index
1
About
Dr. James Rogers is a leading figure in the field of robotic learning and intelligent control systems, with a particular focus on enhancing human-robot interaction and adaptive automation. His most cited work, "BAS Optimized ELM for KUKA iiwa Robot Learning" (2020, 11 citations), introduces a novel approach to robotic learning by integrating the Beetle Antennae Search (BAS) algorithm with Extreme Learning Machines (ELM). This research addresses a critical challenge in robotics—optimizing initial network weights and biases to improve learning performance and stability. By applying this bio-inspired optimization to the KUKA iiwa, a collaborative industrial robot, Rogers has advanced the development of more intuitive and efficient interfaces for robot training. His contributions are particularly significant for the growing field of human-robot collaboration, where safe and adaptive learning is paramount. Through his work, Rogers demonstrates a commitment to bridging computational intelligence with practical robotic applications, making him a notable voice in the evolution of next-generation autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1BAS Optimized ELM for KUKA iiwa Robot Learning11 citations · 2020