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- Title
Fall detection in walking robots by multi-way principal component analysis.
- Authors
J. G. Dani?l Karssen; Martijn Wisse
- Abstract
SUMMARYLarge disturbances can cause a biped to fall. If an upcoming fall can be detected, damage can be minimized or the fall can be prevented. We introduce the multi-way principal component analysis (MPCA) method for the detection of upcoming falls. We study the detection capability of the MPCA method in a simulation study with the simplest walking model. The results of this study show that the MPCA method is able to predict a fall up to four steps in advance in the case of single disturbances. In the case of random disturbances the MPCA method has a successful detection probability of up to 90%.
- Subjects
ERROR detection &; recovery in robotics; ROBOT motion; ROBOT control systems; PRINCIPAL components analysis; COMPUTER simulation; ROBOTICS
- Publication
Robotica, 2009, Vol 27, Issue 2, p249
- ISSN
0263-5747
- Publication type
Article
- DOI
10.1017/S0263574708004645