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基于多传感器融合的全地形机器人系统设计
引用本文:朱颖,吴钰鑫,侯夏嘉,张亚婉,陈庆盛. 基于多传感器融合的全地形机器人系统设计[J]. 计算机测量与控制, 2022, 30(11): 246-250
作者姓名:朱颖  吴钰鑫  侯夏嘉  张亚婉  陈庆盛
基金项目:广东省普通高校青年创新人才项目(NO:2019KQNCX202),2021年广东省科技创新战略专项资金(NO:pdjh2021b0644),2020年广东省大学生创新训练项目(NO:S202013656054)
摘    要:针对因强降雨、堤防溃决、暴雨增水等因素导致的水位突然上升而泛滥和山洪暴发,形成复杂多变灾后的地形环境。设计了以FPGA为控制器的多传感器融合机器人,提高灾后救援效率。该机器人通过GPS为机器人作业划定区域,生命特征仪、力矩仪和空气质量仪等传感器采集环境数据,搭建非线性全地形机器人动态模型,利用六轴陀螺仪和霍尔传感器获取机器人状态,数据经过扩展卡尔曼滤波算法融合以及航迹算法推算后,获得机器人在灾后环境中的实际信息,使得机器人能够按要求进行搜救作业。实验结果表面,多传感器融合的机器人系统,能够在灾后环境完成信息采集与传输,具有较高的稳定性及准确性。

关 键 词:FPGA,多传感器融合,全地形,扩展卡尔曼滤波,信息采集
收稿时间:2022-04-19
修稿时间:2022-05-19

Design of all-terrain robot System based on Multi-sensor fusion
Abstract:Flood and mountain flood caused by sudden rise of water level due to heavy rainfall, dike break, rainstorm and other factors, forming a complex and changeable terrain environment after disaster.??A multi-sensor fusion robot based on FPGA is designed to improve the rescue efficiency after disaster.??The robot by GPS for robot operation defined area, life characteristics of the meter, torque tester and air quality meter sensor to collect environmental data, such as structures, nonlinear all-terrain robot dynamic model, the use of six axis of gyroscope and hall sensor for robot state, data through extended kalman filter algorithm and track fusion algorithm is calculated,??To obtain the actual information of the robot in the post-disaster environment, so that the robot can carry out search and rescue operations as required.??Experimental results show that the multi-sensor fusion robot system can complete information collection and transmission in the post-disaster environment, with high stability and accuracy.
Keywords:FPGA  Multi-sensor fusion   all-terrain   extended Kalman Filter   information acquisition
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