EfficientGrasp: A Unified Data-Efficient Learning to Grasp Method for Multi-fingered Robot Hands

06/30/2022
by   Kelin Li, et al.
0

Autonomous grasping of novel objects that are previously unseen to a robot is an ongoing challenge in robotic manipulation. In the last decades, many approaches have been presented to address this problem for specific robot hands. The UniGrasp framework, introduced recently, has the ability to generalize to different types of robotic grippers; however, this method does not work on grippers with closed-loop constraints and is data-inefficient when applied to robot hands with multigrasp configurations. In this paper, we present EfficientGrasp, a generalized grasp synthesis and gripper control method that is independent of gripper model specifications. EfficientGrasp utilizes a gripper workspace feature rather than UniGrasp's gripper attribute inputs. This reduces memory use by 81.7 to generalize to more types of grippers, such as grippers with closed-loop constraints. The effectiveness of EfficientGrasp is evaluated by conducting object grasping experiments both in simulation and real-world; results show that the proposed method also outperforms UniGrasp when considering only grippers without closed-loop constraints. In these cases, EfficientGrasp shows 9.85 success rate in simulation. The real-world experiments are conducted with a gripper with closed-loop constraints, which UniGrasp fails to handle while EfficientGrasp achieves a success rate of 83.3 failures of the proposed method are analyzed, highlighting ways of enhancing grasp performance.

READ FULL TEXT

page 1

page 2

page 3

page 4

page 6

page 7

research
04/14/2018

Closing the Loop for Robotic Grasping: A Real-time, Generative Grasp Synthesis Approach

This paper presents a real-time, object-independent grasp synthesis meth...
research
03/04/2019

Improving Task-Parameterised Movement Learning Generalisation with Frame-Weighted Trajectory Generation

Learning from Demonstration depends on a robot learner generalising its ...
research
05/26/2022

Grasping as Inference: Reactive Grasping in Heavily Cluttered Environment

Although, in the task of grasping via a data-driven method, closed-loop ...
research
03/30/2022

PEGG-Net: Background Agnostic Pixel-Wise Efficient Grasp Generation Under Closed-Loop Conditions

Performing closed-loop grasping at close proximity to an object requires...
research
05/11/2022

Accelerating Grasp Learning via Pretraining with Coarse Affordance Maps of Objects

Self-supervised grasp learning, i.e., learning to grasp by trial and err...
research
04/03/2023

A Simple Approach for General Task-Oriented Picking using Placing constraints

Pick-and-place is an important manipulation task in domestic or manufact...
research
04/02/2020

CLASH WRIST – A hardware to increase the capability of CLASH fruit gripper to use environment constraints exploration

Humans use environmental constraints (EC) in manipulation to compensate ...

Please sign up or login with your details

Forgot password? Click here to reset