| With the emergence of new materials and the continuous breakthroughs in sensor technology,our life has been affected by various robots in all aspects.It brings a immeasurable development space of the future for our human being.Indoor robots are closely related to people’s living and entertainment.It is gradually playing an increasingly critical role in our daily life.At first problem is itself autonomous navigation and obstacle avoidance problem in known or unknown environment when indoor intelligent autonomous robot to complete their various tasks.So the positioning and navigation technology research is essential problem for a indoor robot.It is also a difficulty and a focus issues of this field both at our country and abroad.Due to the current technological situation and cost,robot indoor positioning has not formed a large-scale and mature market application in the research field.Therefore,the design and implementation of low cost,high precision and reliable indoor positioning navigation is a key problem in the field of robot indoor positioning navigation.The first problem is how to obtain comprehensive environmental information efficiently and reliably when performing tasks in the indoor environment.Therefore,this paper studies the MSIF(multi-sensor information fusion)hierarchy,structure and method at first.In this paper,the problem of incomplete information acquisition of robot environment,low accuracy of positioning navigation positioning and the complex and real-time error of MSIF algorithm are presented.In this paper,the information fusion of various types of sensors,such as MEMS-IMU/Li DAR and Odometer are presented.The problem of low positioning accuracy such as incomplete information of indoor robot environment and sensor error is solved.In addition,the existing indoor robot navigation and positioning method are analyzed in this paper.The current technology&cost &each sensor module and system model of indoor robot are constructed.A simulation experiment environment was established by MATLAB based on Li DAR/IMU’s IEKF data fusion SLAM location algorithm method.The aim is to reduce the positioning error and improve the stability of the system.Based on MSIF indoor robot navigation and positioning,environmental composition and autonomous navigation obstacle avoidance experiment,the influence of indoor robot position and algorithm improvement on positioning navigation accuracy was analyzed based on experimental results.The effectiveness of robot positioning navigation algorithm in indoor environment is verified.Second,this paper is based on Li DAR in the MSIF based on indoor robot SLAM.The automatic obstacle avoidance and navigation algorithm is designed to realize the functions of active avoidance and autonomous path planning,synchronous incremental environment composition,environmental detection and information data terminal monitoring and control.The hardware system and the selection of each hardware module are designed.Besides,the hardware platform of multi-sensor indoor robot is built and the feasibility is analyzed.This paper takes the indoor robot platform as the research object.Display the posture,movement condition and environmental information of the indoor robot in PC terminal.Moreover,the prototype of engineering application test and the mobile terminal APP based on Android are designed to realize the remote mobile terminal information monitoring and sharing.In this paper,the localization and navigation algorithm and the realization of indoor robot positioning verification hardware platform are used to provide references for future research on indoor robot positioning.The design of indoor robot platform is expanded through engineering practice at the same time.Such as mine roadway exploration n,earthquake disaster search,anti-terrorist bombing,military investigation and dangerous environment that pose a threat to the human body and so on.In a word,this method can take a good market application prospect and extensive extension space. |
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