From Unified Robot Description Format to DH Parameters: Examinations of Two Different Approaches for Manipulator
Byeonggi Yu, Junyoung Lee, Sang Hyun Park, Murim Kim
- 发表年份
- 2024
- 引用次数
- 5
摘要
Robot technology is changing exponentially based on rapid hardware and software advancement. However, one of the most important parts of robotics has not changed: where the robot is or what the robot’s configuration is. We need to build a kinematic chain to find a robot configuration. The standard approach to building a kinematic chain in a manipulator was Denavit-Hartenberg(DH) parameters. DH parameters have compact notation and a lot of advantages in aspect of kinematic application. However, it is challenging for novices unfamiliar with DH parameters. The unified robotics description format(URDF) has been introduced rapidly to build a kinematic chain. URDF is easy to read and intuitive for building a kinematic chain. Consequently, some engineers are biased toward URDF. This phenomenon has generated a need for more mutual understanding between the users who prefer DH parameters and those who prefer URDF. Some bridges should be introduced for both sakes. In this paper, we introduce two approaches to constructing DH parameters from URDF: Dummy-frame-based and joint-axis-based approaches. The dummy-frame-based approach focuses on keeping information on URDF. On the other hand, the joint-axis-based approach tries to construct a kinematic chain in the most effective way in the aspect of DH parameters. These approaches can construct kinematic chains which are identical to the kinematic chains from URDF. Moreover, these approaches can provide the same forward dynamic results as URDF. As a result, these approaches could bridge two representations of robot kinematics and help robotics engineers adopt both representations quickly.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002