Todd Charter

About

Dr. Todd Charter is at the forefront of intelligent manufacturing, pioneering the integration of deep reinforcement learning and extended reality to transform industrial automation. His primary research areas encompass machine scheduling optimization, human-robot collaboration, and human-in-the-loop systems. Charter’s seminal work, "Deep reinforcement learning for machine scheduling," has garnered 45 combined citations, establishing a foundational methodology that bridges theoretical AI with practical production planning. His 2024 study on extended reality for enhanced human-robot collaboration introduces a groundbreaking human-in-the-loop framework, demonstrating how immersive technologies can preserve manufacturing flexibility while maintaining automation’s efficiency gains. This work directly addresses the critical tension between productivity and adaptability in modern factories. Charter’s contributions are particularly notable for their interdisciplinary approach, combining reinforcement learning algorithms with real-time human feedback mechanisms. His research has significant implications for Industry 4.0, offering scalable solutions for customized manufacturing environments. With a growing citation impact and pioneering work in both algorithmic scheduling and collaborative robotics, Charter is shaping the future of smart, human-centric manufacturing systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

   30 citations · 2025
2. 2
   Deep Reinforcement Learning for Machine Scheduling: Methodology, the State-of-The-Art, and Future Directions

   15 citations · 2023
3. 3
   Extended Reality for Enhanced Human-Robot Collaboration: a Human-in-the-Loop Approach

   8 citations · 2024

Key Collaborators

Contact & Links