Reducing influence of robot’s motion on tactile sensor based on partially linear model
Taichi Tajika, Takahiro Miyashita, Hiroshi Ishiguro, Norihiro Hagita
- Year
- 2008
- Citations
- 4
Abstract
Robots that are supposed to work and communicate with humans in our daily life have been developed in recent years. For this kind of robots, sensitive tactile sensors are necessary to achieve haptic interactions. However, influences of its own motion on tactile sensors sometimes become larger than the signal to be detected. This paper proposes a method to reduce such noises. It is enabled by estimating and subtracting the influences from sensor outputs. The influences of robotpsilas motions on tactile sensors are estimated by using the sequence of joint angles of the robot. In our method, a partially linear model is built to estimate the influences on a tactile sensor. The robotpsilas posture space, which is represented by its joint angles, is divided into several subspaces to fit to a linear model. We conducted an experiment with a robot covered with tactile sensors to verify the validity of our method. This paper shows that the robot is able to estimate the influences on a tactile sensor in high accuracy by the model.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991