The Grasp Reset Mechanism: An Automated Apparatus for Conducting Grasping Trials
CoRR(2024)
摘要
Advancing robotic grasping and manipulation requires the ability to test
algorithms and/or train learning models on large numbers of grasps. Towards the
goal of more advanced grasping, we present the Grasp Reset Mechanism (GRM), a
fully automated apparatus for conducting large-scale grasping trials. The GRM
automates the process of resetting a grasping environment, repeatably placing
an object in a fixed location and controllable 1-D orientation. It also
collects data and swaps between multiple objects enabling robust dataset
collection with no human intervention. We also present a standardized state
machine interface for control, which allows for integration of most
manipulators with minimal effort. In addition to the physical design and
corresponding software, we include a dataset of 1,020 grasps. The grasps were
created with a Kinova Gen3 robot arm and Robotiq 2F-85 Adaptive Gripper to
enable training of learning models and to demonstrate the capabilities of the
GRM. The dataset includes ranges of grasps conducted across four objects and a
variety of orientations. Manipulator states, object pose, video, and grasp
success data are provided for every trial.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要