The Role of Physics-Based Simulators in Robotics

被引：34
作者：
Liu, C. Karen [1 ]
Negrut, Dan [2 ]
机构：
[1] Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA
[2] Univ Wisconsin Madison, Dept Mech Engn, Madison, WI 53706 USA
来源：
ANNUAL REVIEW OF CONTROL, ROBOTICS, AND AUTONOMOUS SYSTEMS, VOL 4, 2021 | 2021年 / 4卷
基金：
美国国家科学基金会;
关键词：
robot simulation; testing through simulation; virtual prototyping of robots; SPARSITY-ORIENTED APPROACH; NULL SPACE METHOD; DYNAMIC-ANALYSIS; MODEL; MANIPULATION; UNCERTAINTY; PROPAGATION; REDUCTION; EQUATIONS; FRAMEWORK;
D O I：
10.1146/annurev-control-072220-093055
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Physics-based simulation provides an accelerated and safe avenue for developing, verifying, and testing robotic control algorithms and prototype designs. In the quest to leverage machine learning for developing AI-enabled robots, physics-based simulation can generate a wealth of labeled training data in a short amount of time. Physics-based simulation also creates an ideal proving ground for developing intelligent robots that can both learn from their mistakes and be verifiable. This article provides an overview of the use of simulation in robotics, emphasizing how robots (with sensing and actuation components), the environment they operate in, and the humans they interact with are simulated in practice. It concludes with an overview of existing tools for simulation in robotics and a short discussion of aspects that limit the role that simulation plays today in intelligent robot design.
引用
收藏
页码：35 / 58
页数：24
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