Constrained Trajectory Optimization and Force Control for UAVs with Universal Jamming Grippers

Abstract This study presents a novel framework that integrates the Universal Gripper (UG) with Unmanned Aerial Vehicles (UAVs) to enable automated grasping with no human operator in the loop. Grounded in the principles of granular jamming, the UG exhibits remarkable adaptability and proficiency, navigating the complexities of soft aerial grasping with enhanced robustness and versatility. Central to this integration is a uniquely formulated constrained trajectory optimization using model predictive control, coupled with a robust force control strategy, underpinning enhanced levels of automation and operational reliability in aerial grasping. This paradigm, while simple, is a powerful conduit for various applications, ranging from material handling to disaster response, propelling advancements toward genuine autonomy in aerial manipulation tasks. The key contributions of this research include the introduction of a constrained trajectory planning algorithm, and a force control strategy ensuring robust grasping, validated through numerical simulations and virtual experiments.