Fusing Hand Postures and Speech Recognition for Tasks Performed by an Integrated Leg–Arm Hexapod Robot

Abstract

Hand postures and speech are convenient means of communication for humans and can be used in human–robot interaction. Based on structural and functional characteristics of our integrated leg-arm hexapod robot, to perform reconnaissance and rescue tasks in public security application, a method of linkage of movement and manipulation of robots is proposed based on the visual and auditory channels, and a system based on hand postures and speech recognition is described. The developed system contains: a speech module, hand posture module, fusion module, mechanical structure module, control module, path planning module and a 3D SLAM (Simultaneous Localization and Mapping) module. In this system, three modes, i.e., the hand posture mode, speech mode, and a combination of the hand posture and speech modes, are used in different situations. The hand posture mode is used for reconnaissance tasks, and the speech mode is used to query the path and control the movement and manipulation of the robot. The combination of the two modes can be used to avoid ambiguity during interaction. A semantic understanding-based task slot structure is developed by using the visual and auditory channels. In addition, a method of task planning based on answer-set programming is developed, and a system of network-based data interaction is designed to control movements of the robot using Chinese instructions remotely based on a wide area network. Experiments were carried out to verify the performance of the proposed system.