Advanced Control & Planning

Develops the mathematical and algorithmic foundations for safe, efficient, and optimized robotic movement.

Key Topics

• Model-predictive control (MPC)
• Nonlinear and adaptive control
• Image-based visual servoing
• Neuroadaptive control
• Path and motion planning
• Combinatorial optimization

Overview

Control theory is the backbone of robotic movement. Our lab designs advanced controllers that guarantee stability, safety, and efficiency even when robots face unexpected disturbances like strong winds or unpredictable terrain. We specialize in non-linear adaptive control and optimization strategies that allow robots to replan their paths on the fly.