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Cooperative Robotics Field

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Radio signals, succinct macro messages, and even physical signals such as gestures or contact have long been used in communication between robotic agents (Raghunathan 2006). Advances in wireless technology have resulted in simple and effective new ways of relaying information to a central base station for processing cooperative actions (Ray 2005). One of the biggest topics facing researchers and developers of cooperative robot systems for the industry is developing new and effective modes of communication, which has also been explored by software simulation (Wilson 2009). The simulation-based study provides an opportunity to examine multiple interactions in cooperative systems and easily make modifications that allow researchers and developers to experiment, understand, and evaluate intelligent robotic systems before undertaking the timely and costly development processes necessary for an application to industry (Hu and Zeigler 2004).

The simulation also provides a viable means to test theories on hoe disturbance can be handled, resulting in unique approaches, such as digital disturbance compensation for high speed and underwater activities (Yatoh et al. 2007). In industry, offline programming of coordinated systems helps to maximize return on investment (Zhang and Heping 2010).

Swarm Intelligence (SI), in which a large number of very simple individuals aggregate by self-organizing algorithms in order to produce complex coordinated behavior, is being investigated as a method for stimulation of the action of coordinated systems (Caviggia et al. 2002). Swarms often operate on the idea that a signal left in the environment by a previous action will stimulate the performance of the next action by another agent of the swarm, propagating behavior and leading to the emergence of apart systemic behavior, a type of behavior called stigmergic action (Parunak 2003).

Though swarm research in the United States is primarily defence-related, several European collaborative projects are now investigating the practicality of applying SI technology to autonomous, mobile multi-robot systems for industrial use (Bogue 2008). These robots are generally well suited to simple tasks like collecting rocks or sorting mail and are currently of limited industrial use. Other systems, such as dynamically reconfigurable robotic system (DDRS), have also been developed to control cooperative systems by exploring how nature controls multiple element systems.  

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