基于演化特征视觉伺服的多旋翼非线性模型预测控制

IF 3.7 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Autonomous Robots Pub Date : 2024-11-28 DOI:10.1007/s10514-024-10183-3

Sotirios N. Aspragkathos, Panagiotis Rousseas, George C. Karras, Kostas J. Kyriakopoulos

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引用次数: 0

摘要

本文介绍了一种视觉伺服非线性模型预测控制（NMPC）方案，用于使用多旋翼无人飞行器（UAV）自主跟踪移动目标。该方案是为监视和跟踪具有不断变化特征的等高线区域而开发的。NMPC 用于管理输入和状态约束，同时加入了额外的屏障功能，以确保系统安全和最佳性能。所提出的控制方案是在提取和实施描述目标和状态变量特征的全动态模型的基础上设计的。使用装有摄像头的四旋翼无人机进行的实时模拟和实验证明了所提策略的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multirotor nonlinear model predictive control based on visual servoing of evolving features

This article presents a Visual Servoing Nonlinear Model Predictive Control (NMPC) scheme for autonomously tracking a moving target using multirotor Unmanned Aerial Vehicles (UAVs). The scheme is developed for surveillance and tracking of contour-based areas with evolving features. NMPC is used to manage input and state constraints, while additional barrier functions are incorporated in order to ensure system safety and optimal performance. The proposed control scheme is designed based on the extraction and implementation of the full dynamic model of the features describing the target and the state variables. Real-time simulations and experiments using a quadrotor UAV equipped with a camera demonstrate the effectiveness of the proposed strategy.

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来源期刊

Autonomous Robots 工程技术-机器人学

CiteScore

7.90

自引率

5.70%

发文量

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.