基于果蝇算法优化的移动机器人RBPF-SLAM研究

针对基于传统Rao-Blackwellized粒子滤波(Rao-Blackwellised Particle Filter,RBPF)算法的移动机器人在进行同时定位与地图构建(Simultaneous Location and Mapping,SLAM)时易发生粒子退化导致移动机器人位姿估计不准确以及地图一致性较差的问题,提出一种基于果蝇优化算法的RBPF-SLAM算法。该算法将果蝇种群觅食过程中果蝇具有的趋味特性引入RBPF算法,将粒子视为果蝇个体,粒子的适应度值作为空气中食物味道的浓度,利用果蝇优化算法的高寻优能力使粒子向高似然区域移动并不断迭代寻优,以优化粒子种群的整体分布。同时,在果蝇寻优后的新种群中引入自适应交叉变异操作,以增加种群多样性。根据粒子的适应度值确定交叉概率,对配对好的粒子进行自适应交叉操作,再根据变异概率对当前种群的最优粒子进行变异操作,选取适应度值更高的粒子作为当前最优解。采用指数函数步长公式更新粒子状态,增加寻优过程中的搜索距离,有效提高算法的收敛效率。基于ACES building和MIT Killian Court数据集的仿真实验以及移动机器人实机测试结...     

改进联合滤波在GPS/DR组合定位中的应用

根据低成本车辆GPS/DR组合定位系统传感器精度低和计算能力弱的特点,提出一种改进联合卡尔曼滤波(FKF)算法,并简化主滤波器信息融合算法,稍微降低融合精度,提高计算效率。试验结果表明,提出的改进联合滤波算法具有融合精度高、容错性好、计算量小、便于工程实现等优点。     

典型集约化污水处理厂工艺设计——以南京某项目为例

南京大厂污水处理厂新建工程(一期)设计规模9万m³/d，出水执行《城镇污水处理厂污染物排放标准》(GB 18918—2002)一级A标准。介绍和分析了大厂污水处理厂工程设计难点，由此确定一期工程处理的工艺方案选择和设计参数，确定了改良型AAO+磁混凝沉淀+反硝化深床滤池+污泥深度浓缩脱水的处理工艺。通过工艺选择和组团式布局解决了用地紧张的难题，利用先进的设备技术保障准Ⅳ出水达标的可行性。对同类标准工程设计有一定的借鉴意义。     

Evaluation of RAOs of a semi-submersible platform using field measurements: A full-scale model in Caspian sea environmental conditions

The present research investigates the motion response of a semi-submersible platform using measured field data. The Iran-Amirkabir semi-submersible platform (SSP) was considered as full-scale model in operation conditions. First, 14 accelerometer sensors were installed on the platform's hull, and measurements were made in 5 different scenarios in the Caspian Sea environmental conditions. Then, the Response Amplitude Operators (RAOs) for six degrees of motion were extracted using measured accelerator data. The Surge, Sway, and Heave RAOs processed by the Kalman estimation filter, Pitch, Roll, and Yaw RAOs were calculated from the Sensor Array method. Moreover, the boundary element method in ANSYS/AQWA software for the Iran-Amirkabir semi-submersible model was developed, and the RAO results were validated against the extracted field measurements. The obtained results from the Sensor Array method and the Kalman estimation filter are compared with the numerical simulations, which show Root Mean Square Errors of less than 3% and 4%, respectively for rotational and translational movements. The Mean Square Errors between both methods were also close to zero. Therefore, the proposed methods predicted activities of the studied SSP with relatively good accuracy by field data collected in the Caspian Sea.