基于实时操作系统和多智能体的智能自主机器人竞赛框架

D. Calvaresi, Paolo Sernani, Mauro Marinoni, A. Claudi, Alessio Balsini, A. Dragoni, G. Buttazzo
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引用次数: 15

摘要

在现代环境中,与人类互动的机器人很普遍,那些在没有人类监督的情况下执行智能任务的机器人需要考虑到潜在的危险。使机器人能够在导航、绘图、物体识别、跟踪和操作能力方面进行评估。机器人比赛可以追溯到80年代早期,被证明在教育和研究方面很有用。一些比赛的重点是人机交互,尽管它们很少产生能够与人类无缝交互的机器人。造成这种情况的主要原因是缺乏对人类意图的理解和对人类行为的快速反应。换句话说,一个理想的机器人必须能够与人类或其他机器人进行沟通和协调,自主行动,并在实时约束下做出反应。本文提出了一个简化智能机器人开发的新框架,并在真实的机器人竞赛中对其进行了测试。该框架结合了(i)与人类、其他机器人交互的多智能体系统,并执行对象识别和寻路,以及(ii)部署在Erika RTOS上的实时运动控制,以移动机器人并及时对环境变化做出反应。在所考虑的竞争场景中,机器人需要在有限的时间内识别和收集有动态障碍物的有限竞技场中的常见物体,接受来自人类的命令并与其他机器人进行竞争。这种方法证实了多代理系统、计算机视觉和实时系统的强大结合。
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A framework based on real-time OS and multi-agents for intelligent autonomous robot competitions
Robots interacting with human beings are widespread in modern environments, and those performing intelligent tasks without human supervision need to take into account potential criticalities. Making robots compete enable their evaluation with respect to navigation, mapping, object recognition, tracking and manipulation capabilities. Robot competitions date back to the early '80s proving to be useful for educational and research purposes. Several competitions are focused on human-robot interaction, even though they rarely produce as outcome robots capable to seamlessly interact with human beings. The main reason for this is the lack of understanding of human intentions and the failure to rapidly react to human actions. In other words, an ideal robot must be able to communicate and coordinate with humans or with other robots, to act autonomously, and to react under real-time constraints. This paper proposes a new framework to simplify the development of intelligent robots, testing them in a real robot competition. The framework combines (i) a multi-agent system to interact with humans, other robots and perform object identification and pathfinding, and (ii) a real-time motion control deployed on the Erika RTOS, to move the robot and react in a timely fashion to changes in the environment. In the considered competition scenario, the robot is required to identify and collect common objects in a bounded arena with dynamic obstacles in a limited amount of time, receiving commands from humans and competing with other robots. This approach confirms the powerful combination of multi-agent systems, computer vision, and real-time systems.
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