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Developmental Learning of Sensorimotor Models for Control in Robotics
- Source :
- SIAM News, SIAM News, 2014, 47 (7), SIAM News, Society for Industrial and Applied Mathematics 2014, 47 (7)
- Publication Year :
- 2014
- Publisher :
- HAL CCSD, 2014.
-
Abstract
- International audience; Robotics is evolving today toward applications in which robots enter into everyday life and thus need to be able to interact with non-engineers; robots that assist people with disabilities in their homes are an example [5]. For such applications, robots must be able to manipulate and use objects in the human environment that cannot be known and modelled beforehand by engineers. For reasons of safety and energy efficiency, the use of soft materials and soft actuators is flourishing in these applications [12]; difficult control problems arise, however, because the dynamics of these soft materials are difficult to model analytically. For these reasons, a crucial goal has become the development of learning methods that allow robots to acquire models of the dynamics of their own bodies and their interactions with new objects.
- Subjects :
- robotics
learning
[SPI.AUTO] Engineering Sciences [physics]/Automatic
motor primitive
[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO]
[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]
[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]
[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]
inverse models
control
motor learning
developmental learning
[SPI.AUTO]Engineering Sciences [physics]/Automatic
Subjects
Details
- Language :
- English
- ISSN :
- 15579573
- Database :
- OpenAIRE
- Journal :
- SIAM News, SIAM News, 2014, 47 (7), SIAM News, Society for Industrial and Applied Mathematics 2014, 47 (7)
- Accession number :
- edsair.dedup.wf.001..ac4d153e3fadd521c4f0ab1278d8d987