R.E. Gander

About

R.E. Gander is a pioneering researcher in computational motor control, whose work bridges artificial intelligence and biological movement science. Gander’s key research areas include artificial neural network modeling of motor systems, human walking dynamics, and impedance control strategies for biological movement. In his seminal 1992 paper, “A movement pattern generator model using artificial neural networks,” Gander demonstrated how ANN architectures could simulate biological motor control—a novel approach at a time when most neural network research focused on cognition and learning. This foundational work has accumulated 34 citations and opened new pathways for understanding how the brain generates coordinated movement. Gander further advanced the field with his 2002 study, “Model predictive impedance control: application to human walking model,” which introduced a general-purpose control framework capable of adapting to different motor tasks, contrasting sharply with task-specific robotic controllers. Though this work has garnered 3 citations to date, its conceptual innovation—blending predictive control with impedance modulation—offers a compelling model for human locomotion. Gander’s contributions have been recognized in conferences and collaborative projects, notably with F. Towhidkhah, cementing his role as a thoughtful architect of biologically inspired motor control theory.

Research Focus

Key Achievements

Top Papers

1. 1
   A movement pattern generator model using artificial neural networks

   34 citations · 1992
2. 2
   Model predictive impedance control: application to human walking model

   3 citations · 2002

Key Collaborators

Contact & Links