Mobile Robot Behavior Controller Based on Genetic Diagonal Recurrent Neural Network
- Resource Type
- Conference
- Authors
- Du, Yanchun; Li, Yibin; Wang, Guiyue
- Source
- 2007 IEEE International Conference on Automation and Logistics Automation and Logistics, 2007 IEEE International Conference on. :2984-2987 Aug, 2007
- Subject
- Robotics and Control Systems
Computing and Processing
Transportation
Signal Processing and Analysis
Mobile robots
Robot control
Recurrent neural networks
Neurons
Genetic algorithms
Neurofeedback
Control systems
Robot sensing systems
Artificial intelligence
Nonlinear dynamical systems
Diagonal Recurrent Neural Network (DRNN)
Genetic Algorithm (GA)
Mobile Robot Behavior Controller
- Language
- ISSN
- 2161-8151
2161-816X
It is crucial that a robot should have both learning and evolutionary ability to adapt to dynamic environments. This paper proposes a new mobile robot behavior controller based on genetic algorithm (GA) and diagonal recurrent neural network (DRNN). The DRNN has the advantages of time series prediction capability because of its memory nodes, as well as local recurrent and self- feedback connections. Genetic algorithm is introduced to optimize the learning rate and the structure of DRNN in order to achieve better performance. Finally, the GA-DRNN is applied to the mobile robot behavior controller Simulation results show that the controller based on GA-DRNN possesses higher precision, compared with controller based on DRNN.