Trajectory Tracking for UAVs: An Interpolating Control Approach

Building on our previous work, this paper investigates the effectiveness of interpolating control (IC) for real-time trajectory tracking. Unlike prior studies that focused on trajectory tracking itself or UAV stabilization control in simulation, we evaluate the performance of a modified extended IC (eIC) controller compared to Model Predictive Control (MPC) through both simulated and laboratory experiments with a remotely controlled UAV. The evaluation focuses on the computational efficiency and control quality of real-time UAV trajectory tracking compared to previous IC applications. The results demonstrate that the eIC controller achieves competitive performance compared to MPC while significantly reducing computational complexity, making it a promising alternative for resource-constrained platforms.

Mission Planner for UAV Battery Replacement

The paper presents a mission planner for an autonomous unmanned aerial vehicle (UAV) battery management system. The objective of the system is to plan replacements of the UAV's battery on the static battery management stations. The plan ensures that UAVs have sufficient energy to fulfill their long-term mission, which would otherwise be impossible. The paper provides a detailed description of the mission planner and all of its components. The functionality of the planner is successfully demonstrated in simulated multi-UAV multi-station scenarios.

UAV Trajectory Planning with Path Processing

This paper examines the influence of initial guesses on trajectory planning for Unmanned Aerial Vehicles (UAVs) formulated in terms of Optimal Control Problem (OCP). The OCP is solved numerically using the Pseudospectral collocation method. Our approach leverages a path identified through Lazy Theta* and incorporates known constraints and a model of the UAV's behavior for the initial guess. Our findings indicate that a suitable initial guess has a beneficial influence on the planned trajectory. They also suggest promising directions for future research.