DocumentCode :
2719519
Title :
Application of single neuron model to motion planning and control of under-actuated robot by MDP framework
Author :
Kawano, Hiroshi
Author_Institution :
NTT Commun. Sci. Labs., NTT Corp., Kanagawa, Japan
fYear :
2005
fDate :
27-30 June 2005
Firstpage :
237
Lastpage :
242
Abstract :
Motion planning of robots based on the Markov decision process (MDP) is now one of the most important topics of robotics research. In motion planning of robots by the MDP, an efficient way to divide robot motion is essential because discrete expressions of states and transitions are used in the calculation. In preparing the discrete expressions of robot motion, it is important that the motion follows the MDP, second, that the time and the amount of memory for the planning calculation are reduced, and that the maneuverability and smoothness of the robot motion are not lost. This paper proposes a new discrete expression of robot motion that can meet these requirements considering the effect of robot dynamics to robot kinematics. The method uses a continuous-time continuous-variable neuron model, which has the stimulation and adaptation properties. The performance of the proposed method was examined by simulation of the motion planning of an under actuated underwater robot and under actuated manipulator with a free joint. The results show the high reliability and flexibility of the method.
Keywords :
Markov processes; fuzzy control; genetic algorithms; manipulators; motion control; neurocontrollers; path planning; robot dynamics; robot kinematics; Markov decision process; autonomous underwater robot; continuous-time continuous-variable neuron model; free-joint manipulator; genetic algorithm; maneuverability; motion control; motion planning; neural network; nonholonomic robot; reinforcement learning; robot dynamics; robot kinematics; robot motion; single neuron model; under actuated manipulator; under actuated underwater robot; under-actuated robot; Communication system control; Manipulators; Motion control; Motion planning; Neurons; Process planning; Robot control; Robot kinematics; Robot motion; Vehicle dynamics; Discrete expression of robot motion; Markov decision process; autonomous underwater robot; free-joint manipulator; genetic algorithm; neural network; non-holonomic robot; reinforcement learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Robotics and Automation, 2005. CIRA 2005. Proceedings. 2005 IEEE International Symposium on
Print_ISBN :
0-7803-9355-4
Type :
conf
DOI :
10.1109/CIRA.2005.1554283
Filename :
1554283
Link To Document :
بازگشت