具有严格速度约束的自主固定翼飞行器编队控制

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Autonomous Robots Pub Date : 2023-09-13 DOI:10.1007/s10514-023-10126-4
Christopher Heintz, Sean C. C. Bailey, Jesse B. Hoagg
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引用次数: 0

摘要

提出了一种自主固定翼飞行器编队控制算法。期望的车辆间位置是时变的,我们假设至少有一辆车辆可以测量其相对于领导者的位置,领导者可以是队列中的物理成员或虚拟成员。每辆车都用扩展的独轮车动力学建模,包括SO(3)上的方向运动学、速度动力学和对速度的严格约束(即地面速度)。分析结果表明,各车辆均呈指数收敛到期望的相对位置。我们还证明了每辆车的速度满足速度约束。在固定翼飞行器的软件在环仿真和实验中验证了编队算法。为了实现编队控制算法,每辆车都有中回路控制器来确定来自外回路编队控制的滚转、俯仰和油门命令。我们用4架固定翼飞行器进行了SITL仿真,演示了不同通信结构下的编队控制。最后,我们进行了多达3架固定翼飞行器的编队控制实验。
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Formation control for autonomous fixed-wing air vehicles with strict speed constraints

We present a formation-control algorithm for autonomous fixed-wing air vehicles. The desired inter-vehicle positions are time-varying, and we assume that at least one vehicle has access to a measurement its position relative to the leader, which can be a physical or virtual member of the formation. Each vehicle is modeled with extended unicycle dynamics that include orientation kinematics on SO(3), speed dynamics, and strict constraints on speed (i.e., ground speed). The analytic result shows that the vehicles converge exponentially to the desired relative positions with each other and the leader. We also show that each vehicle’s speed satisfies the speed constraints. The formation algorithm is demonstrated in software-in-the-loop (SITL) simulations and experiments with fixed-wing air vehicles. To implement the formation-control algorithm, each vehicle has middle-loop controllers to determine roll, pitch, and throttle commands from the outer-loop formation control. We present SITL simulations with 4 fixed-wing air vehicles that demonstrate formation control with different communication structures. Finally, we present formation-control experiments with up to 3 fixed-wing air vehicles.

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来源期刊
Autonomous Robots
Autonomous Robots 工程技术-机器人学
CiteScore
7.90
自引率
5.70%
发文量
46
审稿时长
3 months
期刊介绍: Autonomous Robots reports on the theory and applications of robotic systems capable of some degree of self-sufficiency. It features papers that include performance data on actual robots in the real world. Coverage includes: control of autonomous robots · real-time vision · autonomous wheeled and tracked vehicles · legged vehicles · computational architectures for autonomous systems · distributed architectures for learning, control and adaptation · studies of autonomous robot systems · sensor fusion · theory of autonomous systems · terrain mapping and recognition · self-calibration and self-repair for robots · self-reproducing intelligent structures · genetic algorithms as models for robot development. The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.
期刊最新文献
Optimal policies for autonomous navigation in strong currents using fast marching trees A concurrent learning approach to monocular vision range regulation of leader/follower systems Correction: Planning under uncertainty for safe robot exploration using gaussian process prediction Dynamic event-triggered integrated task and motion planning for process-aware source seeking Continuous planning for inertial-aided systems
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