Tactile-based Grasp Point Optimization

Introduction:

Unknown object manipulation in hand is a challenge task in multifingered robot hand manipulation community. We have shown a simple but efficient two stages manipulation strategy feasibility--"global finger gaits planning , local object manipulation plan and control". Local plan and control is in charge of moving the object in the robot hand workspace limitation, and the global planner is in charge of managing the fingers switch to facilitate the new cycle local manipulation.

This topic contributes on how to autonomously bridge these two planners by an autonomous regrasp point optimization select algorithm, which will combine the grasp quality and manipulability as the global objective function. This algorithm depends on multifingered-hand coordinately self-exploration manipulation. By planing contact points movement and observing the implementation result, the optimal regrasp points can be obtained. Thanks to the dexterous manipulation control basis, we can realize three passive finger grasping the object stably and one active finger exploring the unknown object surface to find the optimal regrasp point task.

The feasibility of the regrasp point selection algorithm is proven in simulation experiments employing a physics engine providing exact contact information (position,normal vector and contact force). In order to motivate the applicability in real world scenarios, where only coarse and noisy contact information will be available, we also evaluated the performance of the approach when adding artificial noise.

Simulation Experiment:

Fig 1. Irregular object in hand manipulation based on the tactile exploration

Reference paper:

Qiang Li, Robert Haschke, Helge Ritter and Bram Bolder, "Grasp Point Optimization by Online Exploration of Unknown Object Surface",12th IEEE-RAS Intl Conf on Humanoid Robots, 29/11/2012, Osaka, Japan.