The Grasps Under Varied Object Orientation Dataset: Relation Between Grasps and Object Orientation
This work addresses grasp planning efficiency for robotics by leveraging object symmetries, but it is incremental as it focuses on experimental data collection rather than novel algorithms.
The paper investigates how human-planned grasps change with object orientation, finding that stable grasps for pick-and-place tasks can be achieved with a small subset of grasp types and that wrist-related parameters follow a normal distribution, based on 13,440 recorded grasps.
After a grasp has been planned, if the object orientation changes, the initial grasp may not have to be modified to accommodate the orientation change. For example, rotation of a cylinder by any amount around its centerline does not change its geometric shape relative to the grasper. Objects that can be approximated to solids of revolution or contain other geometric symmetries are prevalent in everyday life, and this information can be employed to improve the efficiency of existing grasp planning models. This paper experimentally investigates change in human-planned grasps under varied object orientations. With 13,440 recorded human grasps, our results indicate that during pick-and-place task of ordinary objects, stable grasps can be achieved with a small subset of grasp types, and the wrist-related parameters follow normal distribution.