Proprioception-Based Grasping for Unknown Objects Using a Series-Elastic-Actuated Gripper
March 26, 2018 Β· Declared Dead Β· π IEEE/RJS International Conference on Intelligent RObots and Systems
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Authors
Tianjian Chen, Matei Ciocarlie
arXiv ID
1803.09674
Category
cs.RO: Robotics
Citations
10
Venue
IEEE/RJS International Conference on Intelligent RObots and Systems
Last Checked
4 months ago
Abstract
Grasping unknown objects has been an active research topic for decades. Approaches range from using various sensors (e.g. vision, tactile) to gain information about the object, to building passively compliant hands that react appropriately to contacts. In this paper, we focus on grasping unknown objects using proprioception (the combination of joint position and torque sensing). Our hypothesis is that proprioception alone can be the basis for versatile performance, including multiple types of grasps for objects with multiple shapes and sizes, and transitions between grasps. Using a series-elastic-actuated gripper, we propose a method for performing stable fingertip grasps for unknown objects with unknown contacts, formulated as multi-input-multi-output (MIMO) control. We also show that the proprioceptive gripper can perform enveloping grasps, as well as the transition from fingertip grasps to enveloping grasps.
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