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Evolutionary Robotics: From Algorithms to Implementations

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Modern robotics has moved from the industrial manufacturing environment to human environment for service and entertainment in the recent few years. The human environment is typically unstructured and quite often everchanging, the robot is required to be capable of independently learning the dynamic environment as well as continuously adjusting its behavior to accomplish the desired tasks during its execution. It should be able to capture the properties of the environment effectively and make suitable decisions accordingly to properly deal with the current situation in realtime. In order to accomplish the desired tasks, mobile robots should have a certain level of intelligence to deal with the uncertainties occurred the environment that they are operating in. For instance, if a mobile robot is required to keep track of a moving object, it needs to determine by itself the movement of the target and plan its appropriate path to closely follow the target. Meanwhile, the robot may be asked to execute other tasks such as obstacle avoidance during its motion. However, the pre-programmed robots can not accomplish such tasks adaptively since they have no ability to handle the real operating situations in a smart fashion.
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