Active target search for high dimensional robotic systems
Active target search for high dimensional robotic systems
复制标题
高维机器人系统的主动目标搜索
DOI：
10.1007/s10514-015-9539-8
复制
发表时间：
2015
影响因子：
3.5
通讯作者：
E. Croft
中科院分区：
文献类型：
--
作者：
Sina Radmard;E. Croft
当机器人视觉伺服/跟踪系统看不到目标时，由于输入丢失，伺服系统发生故障。为了解决这一问题，需要一种搜索方法，即丢失目标搜索(LTS)，该方法将产生有效的动作以将目标尽快带回相机视场(FOV)。对于高维平台，如安装在相机上的机械手或手眼系统，这样的搜索必须解决在避免运动学约束的同时以在线方式生成有效动作的困难挑战。在这项工作中，我们利用目标在离开FOV之前的最新可用信息来启动最优在线搜索。我们解释了整个LTS算法的各种特点，并与文献中存在的常见方法进行了仿真比较。最后，我们在实验室规模的7自由度手眼跟踪快速运动目标系统上实现并演示了该通用算法的性能。
When a robotic visual servoing/tracking system loses sight of the target, the servo fails due to loss of input. To resolve this problem a search method, namely a lost target search (LTS) which will generate efficient actions to bring the target back into the camera field of view (FoV) as soon as possible, is required. For high dimensional platforms, like a camera-mounted manipulator or an eye-in-hand system, such a search must address the difficult challenge of generating efficient actions in an online manner while avoiding kinematic constraints. In this work, we utilize the latest available information from the target just prior to leaving the FoV to initiate an optimal online search. We explain various features of our overall LTS algorithm and provide simulation comparisons with common methods existing in the literature. Finally, we implement and demonstrate the capabilities of our general algorithm on a laboratory scale 7 degree of freedom (DoF) eye-in-hand system tracking a fast moving target.