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Exploiting Robot Hand Compliance and Environmental Constraints for Edge Grasps
Joao Bimbo1, Enrico Turco1,2, Mahdi Ghazaei Ardakani3
1Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy.
Frontiers in Robotics and AI
|January 27, 2021
Summary
This study introduces Environmental Constraint Exploitation (ECE) for soft robotic hands to grasp difficult objects. Two strategies, Continuous Slide and Grasp and Pivot and Re-Grasp, are presented for improved grasping robustness.
Area of Science:
- Robotics
- Soft Robotics
- Grasping Manipulation
Background:
- Grasping objects directly from a surface can be challenging for robotic hands, especially soft, underactuated ones.
- Existing methods often require precise object localization and manipulation, increasing planning complexity.
- Leveraging environmental interactions can enhance grasp robustness and reduce computational load.
Purpose of the Study:
- To develop and evaluate novel grasping strategies for soft robotic hands using Environmental Constraint Exploitation (ECE).
- To introduce two distinct ECE strategies: Continuous Slide and Grasp, and Pivot and Re-Grasp.
- To investigate the effectiveness of these strategies across various object types and sizes.
Main Methods:
- Objects are manipulated to the table edge for grasping, utilizing the environment as a constraint.
- The 'Continuous Slide and Grasp' strategy involves sliding the object while maintaining contact until the edge.
- The 'Pivot and Re-Grasp' strategy uses pivoting during sliding, followed by a repositioning grasp.
- A hybrid force-velocity controller manages sliding, and the 'closure signature' model aids grasp planning.
Main Results:
- 320 grasping trials were conducted with a soft hand on a collaborative robot arm, using 16 diverse objects.
- 'Continuous Slide and Grasp' proved effective for smaller objects (e.g., credit cards).
- 'Pivot and Re-Grasp' demonstrated superior performance with larger objects (e.g., books).
- A classifier was trained to automatically select the optimal strategy based on object size and weight.
Conclusions:
- ECE strategies significantly enhance the robustness of soft robotic hand grasps by utilizing environmental interactions.
- The choice between 'Continuous Slide and Grasp' and 'Pivot and Re-Grasp' depends on object characteristics, particularly size.
- This research represents a crucial step towards deploying soft hands in real-world applications by treating the environment as an assistive element.
