| ID | 原文 | 译文 |
| 14095 | 模型以最小化搜索空域为目标,同时满足目标截获概率和雷达的探测约束,实现对不同截获概率需求的搜索空域规划。 | The model aims at minimizing the airspace to be searched‚and can meet the requirements on target interception probability while satisfying radar detection constraints. The model realizes the planning of the airspace to be searched‚which can meet different requirements on interception probability. |
| 14096 | 引入带约束条件的粒子群优化算法对模型进行求解,仿真结果证明了模型的有效性,并与传统方法、遗传算法和人工鱼群算法进行了对比。 | The Particle Swarm Optimization(PSO) algorithm with several constraints is introduced to solve the model. The simulation results have proved the effectiveness of the model and a comparison is made with the traditional method,the genetic algorithm and the artificial fish swarm algorithm. |
| 14097 | 激光雷达相比于视觉传感器具有抗干扰能力强、测量精度高的优势。 | Compared with visual sensors,LIDAR has the advantages of strong anti-interference ability and high measurement accuracy. |
| 14098 | 针对多线激光雷达距离小型障碍物较远时点云数据稀疏、难以进行精确测量的问题,将YOLO与HSV空间颜色直方图匹配结合进行远距离的目标检测,在机器人运动过程中,当检测区域内的激光数据量满足要求时,根据传感器标定结果对此时的激光雷达数据进行聚类、特征点提取与关键参量计算,完成对障碍物的测量。 | But it is difficult to make accurate measurements on the point cloud data which is sparse when multi-line LIDAR is far away from small obstacles. To solve the problem‚YOLO(You Only Look Once) and HSV spatial color histogram matching are combined to perform long-range target detection. In the process of robot motion‚when the amount of laser data in the detection area meets the requirements‚the LIDAR data at this time is clustered,the feature points are extracted‚and the key parameters are calculated based on the sensor calibration results‚so as to complete the measurement of obstacles. |
| 14099 | 使用16线Velodyne激光雷达与工业IDS相机进行方法验证,结果表明,该方法可提高激光雷达数据量7.83倍,即使是运动场景下也能保证测量小型障碍物的最大宽度误差小于2.4%,测距误差小于0.15%。 | A 16-line Velodyne LIDAR and an industrial IDS camera are used for verification of the method.The results show that this method can increase the data volume of LIDAR by up to 7.83 times.Even in motion scenes‚it is guaranteed that the maximum width error of small obstacles is less than 2.4%‚and the distance-measuring error is less than 0.15%. |
| 14100 | 载体机动时,低精度航姿系统无法准确敏感重力矢量,由加速度计输出计算的水平姿态误差较大。 | When there is maneuvering acceleration‚low-accuracy Attitude and Heading Reference System(AHRS) cannot measure the gravity accurately‚which will cause large errors in horizontal attitude‚if we still use the output of the accelerator to calculate the attitude. |
| 14101 | 为了减弱运动加速度的影响,提高机动状态下水平姿态估计精度,提出一种自适应卡尔曼滤波水平姿态估计算法。 | In order to weaken the influence of maneuvering acceleration and improve the estimation accuracy of horizontal attitude when there is maneuvering acceleration‚an adaptive Kalman-filter horizontal-attitude estimation algorithm is proposed. |
| 14102 | 以姿态四元数和陀螺漂移为状态量,四元数姿态更新微分方程为状态方程,加速度计输出为量测量建立伪量测方程。 | A pseudo-measurement equation is established by taking the attitude quaternion and gyro drift as state variables‚taking the quaternion attitude-update differential equation as the state equation‚and taking the output of accelerator as measurement variables. |
| 14103 | 根据加速度计量测更新残差对量测噪声方差阵进行实时估计和动态调节,较好地解决了机动状态下航姿系统水平姿态估计问题,提高了水平姿态估计精度。 | Based on the residual error of accelerator output update‚the variance matrix of measurement noise is estimated in real time and dynamically adjusted. This method solves the problem of horizontal attitude estimation of AHRS under the influence of maneuvering acceleration‚and improves the estimation accuracy of horizontal attitude. |
| 14104 | 跑车试验验证了算法的有效性。 | Driving tests have verified the effectiveness of the proposed algorithm. |