Study On "Human-Robot-Environment" Interaction And Systems Of Intelligent Robot

Recently,under the background of “using robot to replace human”,“fully automatic factory” and “industrial 4.0”,the research on human-machine-environment interaction and intelligent systems of robots is one of the research hotspots of intelligent robot.Our research work focus on the study on human-robot-environment interaction and systems of intelligent robot.In particular,a human-robot-environment interactive reasoning mechanism is proposed.In our designed reasoning mechanism,a simplified feature descriptor is proposed and used in the process of 3D semantic map generation to balance its ability between matching efficiency and object recognition accuracy;the map matching algorithm is optimized to realize the intelligent interaction of human-robot-environment.Our proposed mechanism is designed for non-expert users who have not been trained in programming,and our mechanism can communicate with human beings by natural language;can real-time percept the 3D environment automatically;has the ability of reasoning and interaction based on 3D scene information;can achieve automatic operation after getting clear and complete desire from users.In order to verify the effectiveness of our proposed reasoning mechanism,an experiment platform for human-robot-environment interactive reasoning mechanism is established to verify our proposed algorithms.For the low accuracy problem of WUST-ARM,an IMU(Inertial Measurement Unit)-based iterative pose compensation algorithm is proposed to improve the end-effector pose of low-precision modular manipulator.The main contents of our research work are as follows:(1)A human-robot-environment interactive reasoning mechanism is proposed,which is based on Case-Based Reasoning-Belief-Desire-Intention(CBR-BDI)reasoning mechanism.The human-robot interaction is achieved by Chinese natural language,which is an input of our proposed reasoning mechanism.The robot-environment interaction is achieved by Kinect sensor's 3D object recognitionand semantic map generation;the semantic map is another input of our proposed reasoning mechanism.(2)In the process of 3D semantic map generation,in order to balance the matching efficiency and object recognition accuracy,a simplified algorithm of local feature descriptor in 3D semantic map generation is studied.A general Gray code quantized model of binary feature descriptors is proposed.In our proposed model,different simplified descriptor can be generate by change the parameters of L and N(L is the encoding group length;N is the number of Gray code bits).Our proposed method is applied to a state-of-the-art descriptor Signature of Histogram of Orien Tations(SHOT)to generate new lower memory consumption and high efficient matching descriptor G-SHOT.(3)A dialogue and 3D scene interaction algorithm is proposed to improve the interactivity of the human-robot-environment interactive reasoning mechanism.With representing the case attribution by topic tree;representing the case solution using robot language;and introducing of the dialogue and 3D scene interaction algorithm,the human-robot-environment interactive reasoning mechanism achieves more efficient interaction,reasoning and guidance.When user's desire is incomplete and/or mismatched with the actual scene,robot will take the initiative to guide users through dialogue,and the user's input information will be used to replenish/correct the user's previous desire.At last,system gets the standard and complete desire of users.(4)An IMU-based iterative pose compensation algorithm is proposed to improve the end-effector pose of low-precision modular manipulator.And an experiment platform for our human-robot-environment interactive system is established to verify the proposed algorithms.The methods of intelligent reasoning of robot which are studied in this dissertation makes our robot has the ability of perception(voice interaction,environmental interaction),thinking(reasoning)and makes human-robot interaction becomes more convenient and easy.