Programming an Autonomous Robot Controller by Demonstration Using Artificial Neural Networks

The use of artificial neural networks (ANNs) to control autonomous robots has been quite extensively studied. Also, in recent years researchers have begun to investigate the notion of programming such robots using visual programming control models. Some of this work has focused on developing languag...

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Vydané v:2004 IEEE Symposium on Visual Language and Human Centric Computing s. 157 - 159
Hlavní autori: Best, S.M., Cox, P.T.
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: Piscataway NJ IEEE 2004
IEEE Computer Society
Predmet:
Actuators
Applied sciences
Artificial neural networks
Computer languages
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Concrete
Control theory. Systems
Exact sciences and technology
Impedance matching
Mobile robots
Programming environments
Programming languages
Robot control
Robot programming
Robot sensing systems
Robotics
Software
Visual languages
Autonomous system
Input output
Programming environment
Measurement sensor
Neural network
Modeling
Robot programming
Visual programming
User interface
Distributed control
Visual programming language
Monitoring control system
ISBN:0780386965, 9780780386969
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Popis
Shrnutí:The use of artificial neural networks (ANNs) to control autonomous robots has been quite extensively studied. Also, in recent years researchers have begun to investigate the notion of programming such robots using visual programming control models. Some of this work has focused on developing languages based on various programming and robot visual programming-by-demonstration (PBD) systems. Here we extend the latter approach by proposing a visual PBD environment for autonomous robots based on ANNs. Within this environment, sensor-to-motor rules, called sensorimotor maps, are programmed by employing ANNs to match sensor outputs to actuator inputs. The goal is to create a programming environment in which the end-user is not required to have any knowledge of the underlying control model, ANN programming in this case. In this regard, the current proposal appears more promising than previous attempts using the subsumption model
ISBN:0780386965
9780780386969
DOI:10.1109/VLHCC.2004.42