基于任务执行度量的多机器人协作系统动态带宽分配

IF 3.1 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Malak Slim, Naseem Daher, Imad H. Elhajj
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引用次数: 0

摘要

多机器人系统(MRS)是一个不断发展的研究领域,其研究重点是多个机器人为实现一个共同的全球目标而进行的协作。管理这些系统面临着多项挑战,包括协调、任务分配和通信。在这些挑战中,一个重点领域是设计一种有效的通信方案,以确保机器人的合作并适应任务执行过程中的各种条件。在本文中,我们开发了一种专为 MRS 量身定制的新型通信管理框架,专门解决联网远程操作机器人系统中的动态带宽分配问题。该算法与基于人工势场(APF)算法的半自主编队控制相结合,使每个机器人都能自主避开局部障碍物,并努力与邻近机器人保持理想的编队,而操作员只负责高层控制。常见的动态带宽分配(DBA)算法会根据网络条件和要求为不同的单元分配带宽。而我们提出的 DBA 方案则根据任务执行和系统性能相关因素,动态分配通信流上的可用带宽。具体来说,分配带宽的方式要适应系统环境及其内部状态的变化,包括路径规划器采取的自主行动对 MRS 的影响以及每个机器人控制器的性能。我们提出的算法通过基于性能指标来塑造 MRS 的通信行为,解决了现有方法的局限性,为提高 MRS 的性能和效率提供了一个前景广阔的解决方案。我们在机器人操作系统(ROS)--Gazebo 仿真环境中对一组六架无人飞行器(UAV)进行了仿真测试。结果表明,该方案既能提高机器人系统的性能,又能显著降低带宽消耗。对两个移动机器人的实验测试进一步证明了所提方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic Bandwidth Allocation for Collaborative Multi-Robot Systems Based on Task Execution Measures

Multi-robot systems (MRSs) is a growing field of research that focuses on the collaboration of multiple robots to achieve a common global objective. Managing these systems poses several challenges, including coordination, task allocation, and communication. Among these challenges, a major area of focus is devising an effective communication scheme that ensures robots’ cooperation and adapts to varying conditions during task execution. In this paper, we develop a novel communication management framework tailored for MRSs, specifically addressing dynamic bandwidth distribution in networked teleoperated robotic systems. The algorithm is combined with semi-autonomous formation control based on the Artificial Potential Fields (APF) algorithm, which allows each individual robot to avoid local obstacles autonomously and tries to maintain a desired formation with its neighbors, while the operator is in charge of high-level control only. Common Dynamic Bandwidth Allocation (DBA) algorithms allocate bandwidth to different units based on network conditions and requirements. On the other hand, our proposed DBA scheme dynamically distributes the available bandwidth on communication streams based on factors related to task execution and system performance. In specific, bandwidth is allocated in a way that adapts to changes occurring in the system’s environment and its internal state, including the effect of the autonomous action taken by the path planner on the MRS and the performance of the controller of each individual robot. By addressing the limitations of existing approaches through shaping the communication behavior of the MRS based on performance measures, our proposed algorithm offers a promising solution for improving the performance and efficiency of MRSs. The proposed scheme is tested through simulations on a group of six unmanned aerial vehicles (UAVs) in the Robot Operating System (ROS)-Gazebo simulation environment. The obtained results show the scheme’s capability for enhancing the robotic system’s performance while significantly reducing bandwidth consumption. Experimental testing on two mobile robots further demonstrates the effectiveness of the proposed scheme.

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来源期刊
Journal of Intelligent & Robotic Systems
Journal of Intelligent & Robotic Systems 工程技术-机器人学
CiteScore
7.00
自引率
9.10%
发文量
219
审稿时长
6 months
期刊介绍: The Journal of Intelligent and Robotic Systems bridges the gap between theory and practice in all areas of intelligent systems and robotics. It publishes original, peer reviewed contributions from initial concept and theory to prototyping to final product development and commercialization. On the theoretical side, the journal features papers focusing on intelligent systems engineering, distributed intelligence systems, multi-level systems, intelligent control, multi-robot systems, cooperation and coordination of unmanned vehicle systems, etc. On the application side, the journal emphasizes autonomous systems, industrial robotic systems, multi-robot systems, aerial vehicles, mobile robot platforms, underwater robots, sensors, sensor-fusion, and sensor-based control. Readers will also find papers on real applications of intelligent and robotic systems (e.g., mechatronics, manufacturing, biomedical, underwater, humanoid, mobile/legged robot and space applications, etc.).
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