KNOWLEDGE-BASED CONTROL OF GRASPING IN ROBOT HANDS USING HEURISTICS FROM HUMAN MOTOR-SKILLS

被引：62
作者：
BEKEY, GA
LIU, H
TOMOVIC, R
KARPLUS, WJ
机构：
[1] TELECOM AUSTRALIA RES LABS, ARTIFICIAL INTELLIGENCE SYST SECT, CLAYTON, VIC 3168, AUSTRALIA
[2] UNIV BELGRADE, DEPT ELECT ENGN, BELGRADE, YUGOSLAVIA
[3] UNIV CALIF LOS ANGELES, DEPT COMP SCI, LOS ANGELES, CA 90024 USA
来源：
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION | 1993年 / 9卷 / 06期
基金：
美国国家科学基金会;
关键词：
D O I：
10.1109/70.265915
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The development of a grasp planner for multifingered robot hands is described. The planner is knowledge-based, selecting grasp postures by reasoning from symbolic information on target object geometry and the nature of the task. The ability of the planner to utilize task information is based on an attempt to mimic human grasping behavior. Several task attributes and a set of heuristics derived from observation of human motor skills are included in the system. The paper gives several examples of the reasoning of the system in selecting the appropriate grasp mode for spherical and cylindrical objects for different tasks.
引用
收藏
页码：709 / 722
页数：14
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