Human-Inspired Compliant Strategy for Peg-in-Hole Assembly Using Environmental Constraint and Coarse Force Information
Xiaoqing Li; Rui Li; Hong Qiao; Chao Ma; Liang li
2017
会议名称IEEE/RSJ International Conference on Intelligent Robots and Systems
会议日期September 24–28
会议地点Vancouver, Canada
摘要
Automated assembly, especially peg-in-hole insertion,
is a common task in manufacturing. In particular, the highprecision
assembly is achieved by high-precision manipulator
and sensing system. However, uncertainty and various parts for
assembly are still challenges for robotic assembly, especially for
low-precision robot and sensors. It is noteworthy that human
can implement assembly tasks although the precision of the arm
and hand is not comparable with a common industrial robot,
in which process compliance is the key characteristic of their
motion. In this paper, we present a human-inspired compliant
strategy for peg-in-hole assembly task using the environmental
constraint and coarse force information. In the proposed
strategy, a constraint region is designed for motion planning and
utilized for eliminating the uncertainty of the initial positioning
error of the peg. Force sensor is applied to sense the contact
force of which the direction is used to adjust the movement
of the peg. Therefore, high-precision sensor is not necessarily
required. Inspired by human compliant assembly, a from coarse
to fine adjustment strategy is executed. The contribution of our
strategy is that high precision assembly task can be solved by
low precision system. The constraint region and force guided
directional adjustment have increased the robustness of the
system. The strategy is carried out in simulation for round pegin-
hole assembly task. The experimental results show that the
assembly task can be successfully completed and demonstrate
the effectiveness of our strategy.
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/20239
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
推荐引用方式
GB/T 7714
Xiaoqing Li,Rui Li,Hong Qiao,et al. Human-Inspired Compliant Strategy for Peg-in-Hole Assembly Using Environmental Constraint and Coarse Force Information[C],2017.
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