This study investigates the formation planning problem of tethered multirotor unmanned aerial vehicle (UAV) cooperative transportation with unknown payload and cable length. Normally, the transportation formation and trajectory are given in advance or designed based on the coupled system model. It is challenging to dynamically generate flexible formations in response to changing environments when the payload and cable length are unknown. This paper proposes an online formation planning method for multirotor UAVs. First, by analyzing the tension on cables, we propose some formation criteria and further construct a corresponding performance function of optimization. Then, desired trajectories/formations that can reduce the cost functions are generated by using the admittance model. Next, an estimation-based formation tracking control is designed, which ensures that multirotor UAVs follow the desired trajectories/formations. Finally, numerical simulations and experiments are conducted to demonstrate the effectiveness of the proposed method. Note to Practitioners —This paper is motivated by the formation planning problem of tethered multirotor UAV cooperative transportation. In industry and production applications, a team of multirotor UAVs has a larger load capacity than a single one. Nevertheless, the formation planning of the tethered cooperative transportation is challenging, especially when the payload and cable length are unknown. Rather than give a predefined formation or trajectory, this paper suggests an online formation planning method for multirotor UAVs in case of unknown payload and cable length. The method is implemented through the following three parts: 1) By analyzing the tension on cables, we propose some formation criteria and further construct a corresponding performance function of optimization. 2) By using the admittance model, we generate desired trajectories/formations that can minimize the proposed cost function. 3) By estimating cable tension, we design formation tracking control laws for multirotor UAVs to follow the desired trajectories/formations. The proposed formation planning method does not rely on the knowledge of the payload and length of cables, which makes it can be easily applied to extensive industry, production, and military practice. Finally, numerical simulations and experiments are conducted to demonstrate the feasibility of the proposed method.

In this letter, a self-triggered based coordinate control scheme with low communication requirements is investigated for a team of unmanned aerial vehicles (UAVs) collaboratively transporting a suspended payload. In most existing research on collaborative transportation, the limited communication ability of physical devices has rarely been studied. Hence, this letter suggests a self-triggered cooperative path-following coordinate control scheme for UAVs traveling along a given desired path and synchronously carrying out transportation mission. It is proven that the proposed coordinate control scheme can make communication discrete, thereby significantly reducing the amount of communication. The results of outdoor experiments verify the feasibility of the proposed strategy, and low-frequency communication is demonstrated.

The aim of this study is to investigate the problem of cooperative multi-robot variation parameter design for dynamic formation maneuvers with bearing constraints. Notably, scaling and translation are relatively economical bearing-preserving motions in terms of formation changes. Typically, the variation parameters, i.e., the desired scaling size and translation vector, are designed offline a priori, and it is often challenging to dynamically generate the desired formation in response to a changing ambient environment. This paper proposes an online distributed design method to determine the variation parameters of an entire formation. First, local variation policies are generated by the proposed high-order control barrier functions based on received local excitations from the environment. Subsequently, using the distributed average tracking technique, consensus filters are employed to integrate various local variation policies in a weighted-average manner, which ensures that the bearing is maintained in dynamic formation maneuvers. Finally, numerical simulations and experiments are conducted to demonstrate the effectiveness of the proposed method. Note to Practitioners —This paper is motivated by the neglect of the research on the automatic co-adjustment of the formation variation parameters in most existing formation control schemes, which rely on fixed and pre-defined desired variation parameters (scaling size and translation vector). To address this limitation, this paper suggests an online distributed design method to determine the variation parameters of an entire formation in dynamic ambient environments. The proposed method consists of three parts: 1) By considering received local excitations from the environment as perturbations to asymptotically stable virtual systems, unconstrained local variation policies are generated. 2) By employing high-order control barrier functions, we solve the bounded magnitude constraints for distributed average tracking (DAT) algorithms and the minimum scale constraint for collision avoidance, leading to the generation of constrained local variation policies. 3) By using DAT algorithms, all robots can cooperatively obtain a uniform variation parameter, which is exactly the weighted average of the constrained local variation policies. This ensures that the bearing is maintained in dynamic formation maneuvers. Therefore, the proposed method can be deployed to multi-robot systems in a distributed manner. Finally, numerical simulations and experiments are conducted to demonstrate the feasibility of the proposed method and its potential in industrial applications.

This article investigates the problem of planar affine formation maneuver control with a matrix-valued formation shape variation parameter. The matrix representation renders full degree of freedom (DOF) motion associated with linear mappings in the context of affine transformation. Unlike the typical leader–follower setup, where all the leaders know the prescribed formation information, only a portion of leaders are informed of the matrix parameter in this article. To achieve affine formation stabilization, two types of distributed estimators are developed for the remaining leaders to infer constant and dynamic matrix parameters, utilizing only local displacement measurements. Then, we establish a joint estimation and cooperative control framework, generating corresponding formation shape changes in consistent with the matrix parameter. The system stability and precise estimation convergence are verified via both rigorous theoretical analyses and simulations with large-scale swarms. Finally, experiments conducted on the Crazyflie robots also validate the effectiveness and practicality of the proposed control approach.

Formation flying of multiple unmanned aerial vehicles (UAVs) has attracted much attention for its versatility in cooperative tasks. In this paper, a distributed formation planning method is proposed for UAVs. First, we design a path searching algorithm, swarm-A*, which can enhance the cohesion of a swarm, i.e., preventing the disintegration of the swarm when it encounters an obstacle. Then, after waypoint reallocation, a formation trajectory optimization framework is formulated. Smooth formation trajectories for UAVs to travel safely in obstacle-laden environments can be obtained by solving the optimization problem. Next, a tracking controller based on sliding mode control is designed, ensuring that the UAVs follow the planned formation trajectories under dynamic constraints. Finally, numerical simulations and experiments are conducted to validate the effectiveness of the proposed method.