Cooperative Transport of a Suspended Payload via Two Aerial Robots with Inertial Sensing


Student thesis: Doctoral Thesis

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Award date3 Jan 2023


Micro aerial vehicles have been widely adopted for various application scenarios, such as cinematography, surveillance, and transportation. Among these, the transport of a payload has been an active research topic, including the task carried out by a team of robots. The technical challenges of such operations cover modeling, motion planning, state estimation, and control.

So far, the realization of aerial cooperative transport has been accomplished mostly with the use of precise position feedback from motion capture systems, allowing the full state of the system to be directly used for control. The availability of accurate measurements permits researchers to focus on developing various motion planning and control strategies. However, these solutions are limited to demonstrations in indoor laboratory environments. More recently, the introduction of vision-based estimation methods makes the task feasible to be carried out in a more realistic outdoor environment. Still, the computational demand for vision-based methods renders them unsuitable for smaller flying robots. This motivates us to develop an efficient vision-less framework.

This thesis investigates the problem of realizing cooperative transport of a cable-suspended payload via two aerial robots with minimal sensing and computational requirement. Herein, we adopt the leader-follower paradigm. The payload is suspended by inelastic cables. The objective is to develop a framework for the follower robot to estimate and stabilize the leader-payload-follower system using only feedback from its inertial sensor. By defining the cable angles as the generalized coordinates to describe the state of the multi-body dynamics, we derive the dynamic and measurement models. Since the dynamics of both robots and the payload are coupled via the cables, it becomes possible to deduce the state of the system by sensing the cable tension on the follower robot. To accomplish this, we introduce a two-stage Kalman-based estimator to provide the system state. Then, we show that a linear control strategy is capable of robustly driving the system to the desired state despite the underactuated nature of the leader-payload-follower system.

The vision-less method has been verified through a series of flight experiments. The efficiency and robustness of the scheme enable the cooperative payload transport to be accomplished by two sub-100-g robots with highly limited computational power in both indoor and outdoor environments. To address the IMU drift problem of a flying robot, we further design an attitude estimator for the follower robot based on the knowledge of its relative velocity to the leader robot.

Overall, the main contribution of this work is a framework that enables two flying vehicles without extra sensors to transport a point-mass suspended payload cooperatively.