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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,...
This article explores the possibility of developing robot control software capable of discerning when and if a robot should deceive. Exploration of this problem is critical for developing robots with deception capabilities and may lend valuable insight into the phenomena of deception itself. In this paper we explore deception from an interdependence/game theoretic perspective. Further, we develop...
As robots step into the human's daily lives, interaction and communication between human and robot is becoming essential. For this social interaction with humans, we propose an emotion generation model considering simplicity, believability and uncertainty. First, OCC model is simplified and then stochastic approach on emotion decision algorithm for believability and uncertainty is applied. The proposed...
Laser beam welding is the method of choice for the high-quality joining of materials. However, for industrial production these systems have to be set up and calibrated manually with much effort. Our objective is to apply intelligent data processing that results in a cognitive technical system that can learn how to weld, speed up the configuring process, and reduce costs. While monitoring laser welding...
To enhance the affinity between humans and robots, we have attempted to give a robot "consciousness" and ??emotion?? such as that identified in humans and animals. A hierarchical structure model has been developed to connect the robot's consciousness with the robot's behavior. However, it is difficult to autonomously control the timing that changes the consciousness and behavior of the robot...
The integration of multiagent systems (MAS) with organizations creates a platform to solve a number of real world problems. Extending the use of multiagent organizations to work with physical sensors and robotic systems synergizes the control ability of agents with the ability to monitor and affect physical phenomena. This research effort examines the use of agents, which are embedded into microprocessor...
In this work we refine an initial grasping behavior based on 3D edge information by learning. Based on a set of autonomously generated evaluated grasps and relations between the semi-global 3D edges, a prediction function is learned that computes a likelihood for the success of a grasp using either an offline or an online learning scheme. Both methods are implemented using a hybrid artificial neural...
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