2020
DOI: 10.1177/0278364920947469
|View full text |Cite
|
Sign up to set email alerts
|

Hand closure model for planning top grasps with soft robotic hands

Abstract: Automating the act of grasping is one of the most compelling challenges in robotics. In recent times, a major trend has gained the attention of the robotic grasping community: soft manipulation. Along with the design of intrinsically soft robotic hands, it is important to devise grasp planning strategies that can take into account the hand characteristics, but are general enough to be applied to different robotic systems. In this article, we investigate how to perform top grasps with soft hands according to a … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
16
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
4
2
1

Relationship

0
7

Authors

Journals

citations
Cited by 24 publications
(16 citation statements)
references
References 47 publications
0
16
0
Order By: Relevance
“…Similarly, humans often slide their fingertips across flat surfaces when picking up small objects [2], [3], which has inspired robotic grasping methods [4], [5], [6]. Work on grasping and manipulation with soft end effectors has focused on larger objects than we consider [7], [8], [9]. Larger objects make task performance less sensitive to geometric variation from deformation, such as due to sliding while in contact.…”
Section: Related Workmentioning
confidence: 99%
“…Similarly, humans often slide their fingertips across flat surfaces when picking up small objects [2], [3], which has inspired robotic grasping methods [4], [5], [6]. Work on grasping and manipulation with soft end effectors has focused on larger objects than we consider [7], [8], [9]. Larger objects make task performance less sensitive to geometric variation from deformation, such as due to sliding while in contact.…”
Section: Related Workmentioning
confidence: 99%
“…Amanov et al (2021) validated a model‐based control for a tendon‐driven continuum robot, which was designed on a small scale with diameters of below 10 mm. Pozzi et al (2020) investigated the grasps with soft hands according to a model‐based approach, in which the so‐called closure signature was used to model closure motions of soft hands by associating to them a preferred grasping direction. Bieze et al (2020) investigated a closed‐loop control strategy for a deformable manipulator, which was implemented to account for the disparities between the model and the robot.…”
Section: Enabling Technologies Of the Soft Manipulatormentioning
confidence: 99%
“…This characteristic comes with the additional benefit that potential uncertainties in local relative placement between the end-effector and the object are compensated by the compliance of the hand, thus relaxing constraints in robot planning. [3][4][5][6] However, this increased dexterity is also responsible for a reduced amount of information that the regulator may feedback to close a control loop. Indeed, because of the difficulties in defining accurate models of hands, [7] of the hand-object interaction when softness is involved, [8] and to the intrinsic uncertainties that elastic components produce in the measurements, [9] it is in general not straightforward to use sensing techniques originally developed for rigid end effectors (e.g., rigid force sensors at the fingertips, encoder [10] ), and to implement model-based feedback solutions that can react to unexpected situations.…”
Section: Introductionmentioning
confidence: 99%
“…This characteristic comes with the additional benefit that potential uncertainties in local relative placement between the end‐effector and the object are compensated by the compliance of the hand, thus relaxing constraints in robot planning. [ 3–6 ]…”
Section: Introductionmentioning
confidence: 99%