By Jong-Hwan Kim, Eric T . Matson, Hyun Myung, Peter Xu, Fakhri Karray

ISBN-10: 331905581X

ISBN-13: 9783319055817

ISBN-10: 3319055828

ISBN-13: 9783319055824

We are dealing with a brand new technological problem on the right way to shop and retrieve wisdom and control intelligence for self sufficient companies via clever structures which could be in a position to accomplishing genuine international projects autonomously. to deal with this factor, robotic researchers were constructing intelligence know-how (InT) for “robots that imagine” that is within the concentration of this ebook. The e-book covers all features of intelligence from notion at sensor point and reasoning at cognitive point to behaviour making plans at execution point for every low point phase of the desktop. It additionally offers the applied sciences for cognitive reasoning, social interplay with people, habit iteration, skill to cooperate with different robots, atmosphere knowledge and a man-made genome that may be handed directly to different robots. those applied sciences are to materialize cognitive intelligence, social intelligence, behavioral intelligence, collective intelligence, ambient intelligence and genetic intelligence. The publication goals at serving researchers and practitioners with a well timed dissemination of the new development on robotic intelligence expertise and its functions, in response to a set of papers offered on the on the second overseas convention on robotic Intelligence know-how and functions (RiTA), held in Denver, united states, December 18-20, 2013.

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Extra resources for Robot Intelligence Technology and Applications 2: Results from the 2nd International Conference on Robot Intelligence Technology and Applications

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Theoretically, at one point all springs would be stiff, as all masses would be tightly connected. Putting together the knowledge of how all “masses” are connected with “springs” a map can be created. Figure 3 helps illustrate Graph Based SLAM. Fig. 3. Spring network analogy for the graph based SLAM (taken from [4]) In the figure, as the robot moves several times through the environment the correlations (red links) become increasingly thicker. Since landmarks are fixed, the correlations between landmarks are the thickest.

The first way is realized by planning robots’ final positions prior to deployment of robots [1]−[5]. This planning should be designed for optimizing the communication link, and thus this approach is suitable for static environment rather than dynamic environments. Also, this is useful for cases where a rapid establishment of the network is required, because this way does not require a search task. The second way is realized by deploying a team of leader-follower robots in convoying fashion [6]−[8].

Keywords: transparent obstacle, laser range finder, localization, mobile robot. 1 Introduction To recognize the nearby obstacles rapidly and localize their exact positions accurately is one of the most important problems in the mobile robot navigation. For this problem, there have been many approaches so far such as using sonar sensor [1,2], using robot vision [3,4] and using laser range finder [5,6,7]. Laser range finder is one of the most promising methods in the sense of high accuracy, high resolution and fast measurement speed even though it is very expensive [8].

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Robot Intelligence Technology and Applications 2: Results from the 2nd International Conference on Robot Intelligence Technology and Applications by Jong-Hwan Kim, Eric T . Matson, Hyun Myung, Peter Xu, Fakhri Karray


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