Benchmarking In-Hand Manipulation
Benchmarking In-Hand Manipulation
复制标题
DOI：
10.1109/lra.2020.2964160
复制
发表时间：
2020-01
影响因子：
5.2
通讯作者：
S. Cruciani;Balakumar Sundaralingam;Kaiyu Hang;Vikash Kumar;Tucker Hermans;D. Kragic
中科院分区：
文献类型：
--
作者：
S. Cruciani;Balakumar Sundaralingam;Kaiyu Hang;Vikash Kumar;Tucker Hermans;D. Kragic
这个基准的目的是评估规划和控制方面的机器人手操作系统。目标是评估系统通过使用手指、环境或两者的组合来改变手持物体的姿势的能力。给定一个对象表面网格从YCB数据集，我们提供的初始和目标状态的例子（即静态对象的姿势和指尖位置）的各种手操作任务。我们还提出了度量从特定的初始状态到达目标状态的错误的指标，当在所有任务中聚合时，该指标也可以作为系统的手操作能力的度量。我们提供与基准测试相关的支持软件、任务示例和评估结果。
The purpose of this benchmark is to evaluate the planning and control aspects of robotic in-hand manipulation systems. The goal is to assess the system's ability to change the pose of a hand-held object by either using the fingers, environment or a combination of both. Given an object surface mesh from the YCB data-set, we provide examples of initial and goal states (i.e. static object poses and fingertip locations) for various in-hand manipulation tasks. We further propose metrics that measure the error in reaching the goal state from a specific initial state, which, when aggregated across all tasks, also serves as a measure of the system's in-hand manipulation capability. We provide supporting software, task examples, and evaluation results associated with the benchmark.