Mobile manipulation is essential for robots to accomplish everyday household chores such as set the table. In order to successfully perform manipulation tasks, a 3-D representation of the environment and the pose of the target object are needed. In this article, we propose a systematic solution for safe and efficient robot manipulation. Innovatively, a task-oriented environment modeling strategy is presented for collision-free navigation and motion planning, which integrates the grid-based 2-D map and local real-time octree-based 3-D representation. Furthermore, we introduce a task-oriented object pose estimation approach based on the fiducial marker and ontology technology. In particular, a property-driven target object inference and pose estimation algorithm is designed, which allows the mobile robot to implement the task-oriented object manipulation. The proposed solution is evaluated through real-world experiments, where memory usage, computation time, collision checking, and object pose estimation are extensively investigated. Also, application scenarios are presented to validate the effectiveness and efficiency of our proposal.

中文翻译：

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安全高效的机器人操纵：面向任务的环境建模和物体姿态估计


移动操控对于机器人完成日常家务（例如摆桌子）至关重要。为了成功执行操纵任务，需要环境的 3D 表示和目标对象的姿态。在本文中，我们提出了一种安全高效的机器人操纵系统解决方案。创新性地提出了一种面向任务的环境建模策略，用于无碰撞导航和运动规划，该策略集成了基于网格的 2D 地图和基于局部实时八叉树的 3D 表示。此外，我们引入了一种基于基准标记和本体技术的面向任务的物体姿态估计方法。特别是，设计了一种属性驱动的目标物体推理和位姿估计算法，使移动机器人能够实现面向任务的物体操纵。所提出的解决方案通过真实世界的实验进行评估，其中对内存使用、计算时间、碰撞检查和物体姿态估计进行了广泛的研究。此外，还提出了应用场景来验证我们建议的有效性和效率。