.png){kind=icon}
Return
Fast robot motion generation using principal components: Framework and algorithms
.png){kind=icon}
PRE
AI
DOI：10.1109/TIE.2007.907667.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We present a principal component-based method for generating, in real time, fast robot motions that minimize power consumption. Given a dynamic model of a robot, a sufficiently large set of torque-minimum motions are first obtained for pre-selected initial and final positions that also achieve minimum time while avoiding actuator saturation. These motions are then clustered according to the trajectory endpoints and shape. A principal component analysis is performed for each motion cluster, and the dominant principal components are used as basis functions in a linear interpolation scheme for generating fast, torque-efficient motions between arbitrary initial and final positions. Results obtained for both a six-axis industrial manipulator and a. wheeled mobile robot demonstrate that nearly optimal motions can be obtained in real-time using this scheme.
Keywords:
principal component analysis (PCA)
robot motion generation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.2
Papers:
1.8W
Citations:
9.8W
Organization
Cited Papers
.png){kind=icon}
ShareSaveA novel electrobiotechnology for the recovery of precious metals from spent automotive catalysts
PREAI
ShareSaveShareSaveShareSaveNutrição de mudas de <i>Mimosa caesalpiniaefolia</i> Benth. sob diferentes doses de N, P, K, Ca e Mg
OAAI
OAAIShareSave
View more