Residual Dynamics Learning for Trajectory Tracking for Multi-rotor Aerial Vehicles

Understand

This paper presents a technique to cope with the gap between high-level planning, e.g., reference trajectory tracking, and low-level controlling using a learning-based method in the plan-based control paradigm.

• The technique improves the smoothness of maneuvering through cluttered environments, especially targeting low-speed velocity profiles.
• In such a profile, external aerodynamic effects that are applied on the quadrotor can be neglected.
• Hence, we used a simplified motion model to represent the motion of the quadrotor when formulating the Nonlinear Model Predictive Control (NMPC)-based local planner.