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This article is concerned with autonomous planning of diverse cooperative robot actions. In this work complex cooperative actions are realized based upon the intelligent composite motion control, which is a learning methodology for intelligent robots that gradually realize complex actions from fundamental motions. For efficient construction of action intelligence multi-stage genetic algorithm, MGA,...
As the applications of mobile robot teams become more complex, the impracticality of designing custom solutions is becoming increasingly obvious. A new approach to control system design is required to facilitate the development of modular and scalable systems. Control ad libitum is an approach that decouples the software and hardware design of robot teams, allowing the system to adapt to changing...
Autonomous mobile robots must accomplish tasks in unknown and noisy environments. In this context, learning robot behaviors in an imitation based approach would be desirable in the perspective of service robotics as well as of learning robots. In this work, we use reservoir computing (RC) for learning robot behaviors by demonstration. In RC, a randomly generated recurrent neural network, the reservoir,...
Robocup rescue simulation system is a suitable test-bed for test and evaluation of multi-agent system's related ideas and techniques. Hence, the world robocup competitions are held each year and the used ideas and techniques are evaluated in the form of different teams. In rescue simulation system, at the start of simulation, police agents should search and explore the earthquake area and open the...
Autonomous robotic excavation has often been limited to a single robotic platform using a specified excavation vehicle. This paper presents a novel method for developing scalable controllers for use in multirobot scenarios and that do not require human defined operations scripts nor extensive modeling of the kinematics and dynamics of the excavation vehicles. Furthermore, the control system does not...
In this paper we introduce a framework for self-mobile localization of a group of mobile agents via a novel formation coordination. The key idea of formation coordination is to make an agent move while fixing other agents as reference nodes. Since the mobile agent is connected to the fixed agents, it is localized during the movement. After the movement, the mobile agent is then fixed, and it is used...
As the beginning of the 3D soccer simulation competitions the simulated humanoid robots were used to play soccer in simulated games, this event shifted the aim of the soccer simulation from the design of strategic behaviors into the low level skills like walking and kicking in soccer player itself at first, but by the improvement of these skills new challenge of how to play soccer has been engendered,...
In this paper a novel mechanism for acquiring shared symbols in multi-agent cooperative task is introduced. Inspired by human communication, a technique is suggested in which learning the behaviors and learning how to communicate are decomposed. Decomposing the shared symbol acquisition into two separate learning phases not only simplifies the learning algorithm but also it speeds up the process....
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