Image-Based Estimation, Planning, and Control of a Cable-Suspended Payload for Package Delivery

This letter presents an image-based approach that enables an aerial robot with a cable-suspended mechanism to find a payload with unknown mass, pick it up, transport it, and then put it down at a new location. The pick and place task is performed with minimum cable-swing angle. A new process is presented for state estimation, trajectory planning, and dynamic control using a single onboard camera and inertia measurement unit (IMU). Specifically, a new nonlinear observer, which does not require localization information from external sensors (such as a motion capture system), is created for controlling the robot's velocity. The outer position-control loop is designed in terms of the invariant image feature which is decoupled from the robot's attitude and is proved to be the flat outputs of the system. The combined estimation and control scheme is shown to be asymptotically stable in the Lyapunov sense, where damping due to air contributes to stabilizing the rates of the swing angle. The optimal trajectory of the Euclidean homography is efficiently generated to obtain dynamically-feasible trajectories for the image features. A least-square identification technique is employed to estimate the mass of each payload, and the input shaping technique is implemented to reduce payload swing motion. Finally, a practical package-delivery task is performed to validate the process, where it is shown that the robot can effectively pick up and deliver payloads on command with minimum cable-swing angle.