针对机器人在复杂地形环境下定位不准确、建图精度不高和误差堆积等问题,设计了一种基于优化Hector-SLAM(simultaneous localization and mapping,实时定位与建图)算法的自主导航系统,以实现机器人在及时躲避障碍物的同时准确到达目标...针对机器人在复杂地形环境下定位不准确、建图精度不高和误差堆积等问题,设计了一种基于优化Hector-SLAM(simultaneous localization and mapping,实时定位与建图)算法的自主导航系统,以实现机器人在及时躲避障碍物的同时准确到达目标点。首先,采用双三次插值法代替原有插值法,以解决Hector-SLAM算法在使用低精度激光雷达数据建图时易出现地图不清晰等问题,从而提升扫描匹配的精准度。其次,采用扩展卡尔曼滤波算法对里程计和惯性测量单元的数据进行融合,以提高定位的准确性。再次,针对激光点数据无法瞬时获得而机器人持续运动所导致的运动畸变问题,结合里程计辅助法与PL-ICP(point to line iterative closest points,点到线迭代最近点)配准法,以实现运动畸变的校正;同时,设置倾斜角阈值以消除地图重影,并利用A*算法和动态窗口法规划最优路径。最后,以AGV(automated guided vehicle,自主导引车)为例,在实际场景中开展建图实验和自主导航实验。结果表明,优化后自主导航系统的平均建图相对误差约为0.44%,最小建图误差为0.236 m,较优化前减小了0.041 m,有效地解决了因误差堆积和运动畸变而导致的建图不清晰问题,增强了AGV在复杂地形环境中的适应能力,实现了高精度定位。研究结果对提高移动机器人在室内多障碍物环境下的自主导航能力具有一定的理论和工程意义。展开更多
Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fix...Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fixed threshold voltage value for gray scale display.In addition,the display has to repeatedly refresh between white and black states to eliminate ghost image when it needs to update a new image.The traditional driving waveform for the EPD includes four stages: erasing the original image,resetting to black state,clearing to white state,and writing a new image.A flicker can be found when transferring between two adjacent stages.A new driving waveform based on the improvement of activation pattern is proposed to weaken the ghost image and reduce the flicker.Experimental results show that the proposed driving waveform could weaken the ghost image effectively and reduce the number of flickers by 50%.Compared with the traditional driving waveform,the driving waveform of this work has a better performance.展开更多
文摘针对机器人在复杂地形环境下定位不准确、建图精度不高和误差堆积等问题,设计了一种基于优化Hector-SLAM(simultaneous localization and mapping,实时定位与建图)算法的自主导航系统,以实现机器人在及时躲避障碍物的同时准确到达目标点。首先,采用双三次插值法代替原有插值法,以解决Hector-SLAM算法在使用低精度激光雷达数据建图时易出现地图不清晰等问题,从而提升扫描匹配的精准度。其次,采用扩展卡尔曼滤波算法对里程计和惯性测量单元的数据进行融合,以提高定位的准确性。再次,针对激光点数据无法瞬时获得而机器人持续运动所导致的运动畸变问题,结合里程计辅助法与PL-ICP(point to line iterative closest points,点到线迭代最近点)配准法,以实现运动畸变的校正;同时,设置倾斜角阈值以消除地图重影,并利用A*算法和动态窗口法规划最优路径。最后,以AGV(automated guided vehicle,自主导引车)为例,在实际场景中开展建图实验和自主导航实验。结果表明,优化后自主导航系统的平均建图相对误差约为0.44%,最小建图误差为0.236 m,较优化前减小了0.041 m,有效地解决了因误差堆积和运动畸变而导致的建图不清晰问题,增强了AGV在复杂地形环境中的适应能力,实现了高精度定位。研究结果对提高移动机器人在室内多障碍物环境下的自主导航能力具有一定的理论和工程意义。
基金Project(2011D039)supported by Guangdong Innovative Research Team Program,China
文摘Electrophoretic display(EPD) technology has become one of the main supporting pillars of the electronic paper display industry.Despite its benefits,the EPD technology suffers from several disadvantages such as non-fixed threshold voltage value for gray scale display.In addition,the display has to repeatedly refresh between white and black states to eliminate ghost image when it needs to update a new image.The traditional driving waveform for the EPD includes four stages: erasing the original image,resetting to black state,clearing to white state,and writing a new image.A flicker can be found when transferring between two adjacent stages.A new driving waveform based on the improvement of activation pattern is proposed to weaken the ghost image and reduce the flicker.Experimental results show that the proposed driving waveform could weaken the ghost image effectively and reduce the number of flickers by 50%.Compared with the traditional driving waveform,the driving waveform of this work has a better performance.
