具有环境感知和人机交互能力的多智能体移动机器人系统

M. Tornow, A. Al-Hamadi, Vinzenz Borrmann
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引用次数: 6

摘要

多智能体机器人系统可以作为一个分布式传感器网络,在危险环境中加速探索或搜救行动。每个机器人(例如Eddi机器人)配备了一个2D/3D传感器(MS Kinect)和其他传感器,需要有效地与其他小组成员交换收集到的数据,以进行任务规划。对于环境感知,从机器人旋转时获得的一系列图像生成2D/3D全景图。此外,2D/3D传感器数据用于基于手势和手势的人机交互。该方法利用人工神经网络(ANN)对提取的手部形状的余弦描述子(COD)、胡矩和几何特征组成的特征向量进行处理,实现手部姿态分类。该系统实现了93%以上的整体分类率。它是用在基于手的姿势和手势的人机界面来控制机器人团队。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-agent mobile robot system with environment perception and HMI capabilities
A multi-agent robot system can speed up exploration or search and rescue operations in dangerous environments by working as a distributed sensor network. Each robot (e.g. Eddi Robot) equipped with a combined 2D/3D sensor (MS Kinect) and additional sensors needs to efficiently exchange its collected data with the other group members for task planning. For environment perception a 2D/3D panorama is generated from a sequence of images which were obtained while the robot was rotating. Furthermore the 2D/3D sensor data is used for a Human-Machine Interaction based on hand postures and gestures. The hand posture classification is realized by an Artificial Neural Network (ANN) which is processing a feature vector composed of Cosine-Descriptors (COD), Hu-moments and geometric features extracted of the hand shape. The System achieves an overall classification rate of more than 93%. It is used within the hand posture and gesture based human machine interface to control the robot team.
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