Bruce R. Copeland
Papers
1
Total Citations
2
H-Index
1
About
Bruce R. Copeland is a researcher whose work lies at the intersection of robotics, neural networks, and adaptive control systems. His most notable contribution addresses the complex challenge of coordinating two robot manipulators as they jointly grasp a rigid object without slippage—a problem critical to advanced manufacturing and collaborative robotics. Copeland’s approach leverages a Hopfield neural network to implement an adaptive load apportioning strategy, requiring wrist force/torque sensors on each arm to precisely manage both the forces and torques applied. This dual-control framework enables stable, coordinated manipulation, offering a sophisticated solution to interactive control in multi-arm systems. While his highly specialized work has garnered modest citation counts, it demonstrates a deep engagement with foundational problems in robotic coordination and neural control. Copeland’s research provides a valuable reference for those exploring neural-network-based approaches to force distribution and cooperative manipulation in robotics.
Research Focus
Key Achievements
Top Papers
- 1Two arm adaptive load apportioning using a Hopfield neural net2 citations · 2002