Proprioception-Based Grasping for Unknown Objects Using a Series-Elastic-Actuated Gripper

被引:0
|
作者
Chen, Tianjian [1 ]
Ciocarlie, Matei [1 ]
机构
[1] Columbia Univ, Dept Mech Engn, New York, NY 10027 USA
来源
2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) | 2018年
关键词
HAND; MANIPULATION; FINGERS; DESIGN;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:6675 / 6681
页数:7
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