Formation Tracking with Prescribed Performance and Collision Avoidance

Real-time distributed trajectory planning for mobile robots

This article studies the formation and trajectory tracking control of multiagent systems. We present a novel multilayer graph for the multiagent system to enable extensibility of the interaction network. Based on the multilayer graph, a formation control law by using the potential function approach is developed for autonomous formation, formation maintenance, collision, and obstacle avoidance. When the desired formation is achieved, the barycentric of the formation shape is viewed as a virtual leader, and a model predictive control (MPC) scheme is applied to the virtual leader for tracking a reference trajectory; meanwhile, the agents will maintain the desired angles and distances via the formation control law. By applying the proposed schemes, the tasks of formation maintenance and trajectory tracking in a constrained space are fulfilled. Comprehensive simulation studies under different environmental constraints and trajectories confirm the effectiveness of the proposed approaches in addressing the formation and trajectory tracking problems.

Formation tracking control for underactuated surface vehicles with actuator magnitude and rate saturations

The new era of commercializing space missions introduced a new mindset and mission design paradigms of multi-satellite missions. This is trending in different satellite industry applications such as Earth observation and satellite communication as it is simple, cheap and increases the system robustness. Multi-satellite missions introduced different lines of development like constellations, trail formation and swarm formations to fit different type of missions requirements. Inspired by the Space Ultra-Low Frequency Radio Observatory (SULFRO) project, based on the concept of a constellation of a micro-satellite mothership and 12 nano-satellite daughters, designed for sky observation and space discovery, in this paper, we propose a model of decentralized swarm formation without using a centralized coordination. The proposed method is based on the assumption that micro-satellite share relative position of the formation and communicate through high speed inter-satellite link. Assuming a 2D space for the micro-satellite formation and deployment, the proposed methodology succeeded to deploy the 12 micro-satellites in their targeted formation. The proposed methodology consists of three states that are: Formation Tracking, Movement Control and Collision Avoidance. These three states contributed in the success of the methodology by ensuring that the micro-satellite share the positions and track the new formation needed to ensure the stability and safety of the micro-satellite swarm. The paper also investigated the power consumption of the system and the system stability. The proposed methodology is simulated in three different validation scenarios and successfully achieved the required formation.

We investigate the distributed time-varying formation tracking of networked quadrotors with input saturation and moving obstacles. The quadrotors’ position and attitude models are subjected to unknown external disturbances. This study has two main contributions. First, we develop filter-based distributed desired profiles and extended state observers (ESOs) for state-transformed nonlinear quadrotors to achieve time-varying formation tracking without requiring the velocity and acceleration information of the leader, followers, and moving obstacles. This achievement holds even in the presence of input saturation. Second, the proposed approach guarantees collision avoidance with moving obstacles, including adjacent quadrotors and unknown objects, by using only the relative distance from the obstacle, irrespective of external disturbances. This is accomplished by designing error functions for avoiding moving obstacles and including auxiliary signals in the formation tracker design. Based on the distributed profiles and the signals estimated using the ESOs, we design a collision-free time-varying formation tracker. The Lyapunov stability theory is utilized to prove that all signals of the proposed closed-loop formation tracking system are bounded, and the tracking errors converge to an adjustable bound that includes the origin. Finally, simulation results are provided to demonstrate the effectiveness of the proposed method.

This paper investigates the formation control problem of multi-UAV systems in the presence of switched trajectories and time-varying communication topologies. A distributed formation control protocol is proposed to enable UAVs to track piecewise continuous trajectories while the underlying communication network switches among a finite set of directed graphs. Sufficient and necessary conditions for achieving accurate formation tracking under dual-switching scenarios are derived through stability analysis while the stability of the overall switched system is proven by using multiple Lyapunov functions. To ensure collision avoidance during both trajectory and topology transitions, control barrier functions (CBFs) are employed to construct safety sets, and a quadratic programming(QP)-based optimization framework is designed to modify control inputs in real time. Simulation results demonstrate that the proposed approach effectively coordinates formation tracking, topology switching, and inter-agent safety, offering a solution for UAV collaboration in dynamic and uncertain environments.

In this paper, virtual structure and artificial potential field (APF) based strategies are integrated to realize formation tracking control for a team of unicycles with collision avoidance property. Using virtual structure, each vehicle is required to track a virtual local leader (VLL) for formation maintenance. For inter-vehicle collision avoidance, the motion of each vehicle is restricted in a specified sector area containing the VLL. APF based and backstepping techniques are utilized to design controller that simultaneously satisfy these control objectives.

Connectivity preservation and collision avoidance in networked nonholonomic multi-robot formation systems: Unified error transformation strategy

This brief investigates the flexible leader–follower formation tracking problem for a group of nonholonomic mobile robots, while most of the formation control related work in the literature focuses on the rigid formation. The flexible formation discussed in this brief is defined in curvilinear coordinates in terms of longitudinal separations between robots along the reference trajectory and lateral deviations with respect to this trajectory. Unlike the previous studies on flexible formation control, this brief is under a more challenging assumption that the global position and orientation measurements are not available. To obtain the relative pose relationships amongst robots, a stereo camera is mounted on each follower. In consideration of the fact that visual observations are noise-corrupted and intermittently available, a particle filter-based relative pose estimation approach is employed to estimate the position and orientation of the leader in the local reference frame of the follower using the polluted and discontinuous information. Also, to form a flexible formation, the leader historical trajectory is reconstructed with respect to the current local frame attached on the follower, based on which a reference point is generated. In addition, this brief considers the situation where robots operate in unknown obstacle environments. To ensure robot safety in such environments, a multiobjective control law is proposed to balance reference tracking and collision avoidance in different situations. Simulation and real-robot experiment have been performed to demonstrate the efficacy of the proposed method.

This study addresses the heterogeneous formation control problem for cooperative unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) operating under input quantization constraints. A unified mathematical framework is developed to harmonize the distinct dynamic models of UAVs and USVs in the horizontal plane. The proposed control architecture adopts a hierarchical design, decomposing the system into kinematic and dynamic subsystems. At the kinematic level, an artificial potential field method is implemented to ensure collision avoidance between vehicles and obstacles. The dynamic subsystem incorporates neural network-based estimation to compensate for system uncertainties and unknown parameters. To address communication constraints, a linear quantization model is introduced for control input processing. Additionally, adaptive control laws are formulated in the vertical plane to achieve precise altitude tracking. The overall system stability is rigorously analyzed using input-to-state stability theory. Finally, numerical simulations demonstrate the effectiveness of the proposed control strategy in achieving coordinated formation control.

Localization and tracking of multiple quadrotors with collision avoidance: Theory and experiment

This article addresses the robust formation tracking control problem for multiple underactuated autonomous surface vehicles (ASVs) subject to bounded unknown disturbances. A high-order control barrier function (HOCBF) based collision avoidance formation tracking framework is proposed which combines a nominal controller and the HOCBF induced collision avoidance conditions. First, a predefined-time observer based nominal controller is proposed for the multi-ASV system which achieves formation tracking under general directed communication graphs. Then, a novel HOCBF based collision avoidance method is proposed for ASVs modeled by elliptical shapes to reduce conservatism introduced by conventional circular occupancy area assumptions. Finally, local quadratic optimization problems are established for the ASVs such that the robust collision avoidance formation tracking is achieved with minimal deviation from the nominal trajectories. Extensive simulation and physical experiments are conducted to verify the effectiveness of the proposed control strategy.

The artificial potential function (APF) is a widely applied algorithm in collision-free formation control in multiagent systems (MASs). However, it suffers from oscillations and acceleration surges, particularly when the current formation and the desired one conflict. To address this problem and enhance collision-free formation control in MAS, this article introduces the time-derivative of APFs. This approach unifies attractive and repulsive APFs. The gradients of the APFs transform potential and kinetic energy, and the time-derivative of the APF gradients serve as damping terms to dissipate energy. This article discusses the general properties of APFs and introduces a time-variant formation tracking scheme that encompasses existing algorithms as specific instances. Then, a collision-free formation control algorithm is presented. This article gives proof of its Lyapunov stability and collision avoidance ability, followed by a maneuverability analysis from the geometry perspective. By incorporating the time-derivatives of repulsive APF gradients as damping terms, the proposed method mitigates oscillations and acceleration surges caused by conflicting attractive and repulsive effects.

This work addresses the practical problem of distributed formation tracking control of a group of quadrotor vehicles in a relaxed sensing graph topology with a very limited sensor set, where only one leader vehicle can access the global position. Other vehicles in the formation are assumed to only have access to inter-agent bearing (direction) measurements and relative velocities with respect to their neighbor agents. A hierarchical control architecture is adopted for each quadrotor, combining a high-gain attitude inner-loop and an outer-loop bearing-based formation controller with collision avoidance augmentation. The proposed method enables a group of quadrotors to track arbitrary bearing persistently exciting desired formations, including time-varying shapes and rotational maneuvers, such that each quadrotor only requires relative measurements to at least one neighboring quadrotor. The effective performance of the control strategy is validated by numerical simulations in MATLAB and real-world experiments with three quadrotors.

Searching and containing dynamic target like oil spillage in the ocean is a challenging task due to the natural time variance of the spread of the oil. The use of cooperative multi-marine vehicle systems in a cluttered environment for this purpose poses difficulties in sustaining formation pattern to pursue and contain the leakage. In this article, in order to provide realistic setup for the industrial applications of multi-marine vehicles systems, we present a novel approach for collision-free distributed formation control for a network of underactuated surface vessels (USVs). The proposed approach comprises two layers: A distributed coordination layer and a local fixed-time neural network control layer. In the first layer, formation leaders accomplish a specified formation configuration while tracking a desired trajectory from a tracking leader. The second control layer is to robustly drive the real USVs with parametric and nonparametric uncertainties to track their corresponding formation leaders. Because only parts of the formation leaders can acquire the states of the tracking leader, a distributed fixed-time estimator is proposed to obtain accurate estimations of the desired information for each USV in the network. Next, in order to effectively maneuver in cluttered environment, local path replanning-based repulsive potential function technique is proposed for each USV in the group formation to act on the formation leaders trajectories. Further, redesigned adaptive neural networks are integrated to compensate the model uncertainties. The stability of the proposed controller is verified by the Lyapunov direct method. Simulation studies of a hexagon formation are presented to illustrate the effectiveness of the proposed approach.