Joint Behavioural Control of Autonomous Multi-Robot Systems for Lead-Follower Formation to Improve Human-Robot Interaction

M. Nnennaya, Etse-Oghena Akpaibor, Akash P. Borate, Aakash G. Deshpande, F. Lewis
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引用次数: 1

Abstract

The effective autonomous cooperation between unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has led to an increase in research and development for improving human robot interaction, due to their high potential for achieving successful missions in challenging environments. In this paper, a voice command system is developed to control a UAV and a vision-based approach system controls the UGV in a lead-follower formation to enhance human-robot teams for military defence and rescue missions in urban areas. The proposed voice control framework is executed using open source interface, Robot Operating System (ROS), for aerial vehicle communication supported by spoken dialogues using a wireless microphone, while the UGV detects and tracks a target image captured by the on board low-cost camera from the height of the UAV, using the proposed vision-based approach. The lead-follower formation is based on communication and visibility between the UAV and UGV in a given environment. In addition, a speech recognition module translates voice input to text and the published text is then mapped to the control input of the UAV in order to execute corresponding voice commands. The relative distance and position between the UAV and UGV is estimated from the image received via laptop. UGVs and UAVs have sophisticated design features such as network device communication, navigation, vision sensors and obstacle detection sensors. The UAV is a quad-copter that leads the UGV to accessible areas, while the UGV plays the role of the follower with wheel activators to track and locate the target image on the UAV, given a defined geographic path. The joint behavioural control system of the proposed voice command and vision-based approach is verified by experimental setups that show the UAV has a high voice recognition response and the UGV autonomously tracks the moving UAV in real time operation. As a consequence of the experimental tests, it is expected that the voice control system and vision-based approach developed play an important role in future combat fields.
基于引导者-从者编队的自主多机器人系统联合行为控制改进人机交互
由于无人机(uav)和无人地面车辆(ugv)在具有挑战性的环境中实现成功任务的巨大潜力,因此无人机(uav)和无人地面车辆(ugv)之间的有效自主合作导致了改善人机交互的研究和开发的增加。本文提出了一种语音指挥系统来控制无人机,一种基于视觉的进近系统来控制无人潜航器,以增强人-机器人团队在城市地区的军事防御和救援任务。提议的语音控制框架使用开源接口机器人操作系统(ROS)执行,用于使用无线麦克风支持语音对话的飞行器通信,而UGV使用提议的基于视觉的方法从无人机的高度检测和跟踪机载低成本摄像机捕获的目标图像。引导-跟随编队是基于在给定环境中UAV和UGV之间的通信和可见性。此外,语音识别模块将语音输入转换为文本,然后将发布的文本映射到UAV的控制输入,以便执行相应的语音命令。根据笔记本电脑接收到的图像估计无人机与UGV之间的相对距离和位置。ugv和无人机具有复杂的设计特征,如网络设备通信,导航,视觉传感器和障碍物检测传感器。UAV是一种四旋翼飞行器,引导UGV到达可到达的区域,而UGV扮演跟随者的角色,带轮子激活器跟踪和定位UAV上的目标图像,给定一个定义的地理路径。实验验证了基于语音命令和视觉的联合行为控制系统,表明无人机具有较高的语音识别响应,并且UGV在实时操作中自主跟踪移动的无人机。通过实验测试,期望所开发的语音控制系统和基于视觉的方法在未来的作战领域发挥重要作用。
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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