Titlebook: Soft Computing for Intelligent Robotic Systems; Lakhmi C. Jain,Toshio Fukuda Book 1998 Springer-Verlag Berlin Heidelberg 1998 Intelligente

Defense

Insul岛

Artificial Immune Network and Its Application to Robotics,rs, therefore, much attention has been focused on the reactive planning approach such as behavior-based AI. However, in the behavior-based artificial AI approach, there are following problems that have to be resolved: 1) how do we construct an appropriate arbitration mechanism, and 2) how do we prep

DIS

Intelligent Optimal Design of CMAC Neural Network for Robot Manipulators,metic Computer (CMAC) neural networks. Explicit solutions to the Hamilton-Jacobi-Bellman (H-J-B) equation for optimal control of robotic systems are found by solving an algebraic Riccati equation. It is shown how CMAC can cope with nonlinearities through optimization with no preliminary off-line lea

Obscure

Hierarchical Behavior Controller in Robotic Applications,ies for robot’s actuators. This algorithm selects the subcontroller which is not appropriate and needs to be tuned, by evaluating each subcontroller using multiple regression analysis based on previously obtained evaluation values. This can reduce the learning iterations by avoiding attempts to tune

初学者

Neural Reinforcement Learning for Robot Navigation,wanted behavior. This measure correspond to a qualitative evaluation of the agent behavior. An agent means here a simulated system in a virtual world or a real agent interacting with a real world. The agent perceives situations of the world with its sensors and acts in the world with its motors. Fig

LAITY

Neural Fuzzy Techniques in Sonar-Based Collision Avoidance,ll first provide the reader with a brief overview of existing concepts of neuro-fuzzy control and then present our own approach based on Radial Basis Functions. This particular Fuzzy-RBF (FRBF) approach is innovative w.r.t. three aspects of neuro-fuzzy control. First, it alleviates the covering prob

BABY

Trends in Evolutionary Robotics, and have been tested on actual physical robots. The chapter also examines the role of simulation and the use of domain knowledge in the evolutionary process. It concludes with some predictions about future directions in robotics.

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Hierarchical Behavior Controller in Robotic Applications,havior controller in order to compensate imperfect initial controllers. The hierarchical behavior controller is applied to the problem of controlling a seven-link brachiation robot, which moves dynamically from branch to branch like a gibbon, a long-armed ape, swinging its body in a pendulum (Figure 1).