Autonomous Hook-Based Grasping and Transportation with Quadcopters

TL;DR

This work tackles autonomous payload grasping and transportation with a quadrotor using a lightweight, passive $1$-DoF hook manipulator. It introduces a time-optimal trajectory planning framework across five segments and a two-stage control strategy that combines a robust geometric controller with a linear–quadratic payload regulator to damp payload swing, supported by a switching stability analysis. The approach is validated in high-fidelity MuJoCo simulations and real-world flight experiments on a custom quadrotor–hook platform, demonstrating precise payload pickup, transit, and release with robustness to payload mass variations. The findings suggest a practical, scalable solution for passive aerial manipulation that minimizes added weight and power consumption while maintaining agile performance in autonomous transportation tasks.

Abstract

Payload grasping and transportation with quadcopters is an active research area that has rapidly developed over the last decade. To grasp a payload without human interaction, most state-of-the-art approaches apply robotic arms that are attached to the quadcopter body. However, due to the large weight and power consumption of these aerial manipulators, their agility and flight time are limited. This paper proposes a motion control and planning method for transportation with a lightweight, passive manipulator structure that consists of a hook attached to a quadrotor using a 1 DoF revolute joint. To perform payload grasping, transportation, and release, first, time-optimal reference trajectories are designed through specific waypoints to ensure the fast and reliable execution of the tasks. Then, a two-stage motion control approach is developed based on a robust geometric controller for precise and reliable reference tracking and a linear--quadratic payload regulator for rapid setpoint stabilization of the payload swing. Furthermore, stability of the closed-loop system is mathematically proven to give safety guarantee for its operation. The proposed control architecture and design are evaluated in a high-fidelity physical simulator, and also in real flight experiments, using a custom-made quadrotor--hook manipulator platform.

Figures (8)

• Figure 1: Payload transportation by a hook-based manipulator.
• Figure 2: Coordinate frames describing the geometric relations of the quadcopter and the environment.
• Figure 3: Motion trajectory segments and waypoints.
• Figure 4: Schematic trajectory of the yaw angle reference.
• Figure 5: Block diagram of the closed-loop control scheme with scheduling of the controllers along the motion trajectory (C1: geom. with feedforward, C2: geom., C3: LQR).