By Andreas Birk, Silvia Coradeschi, Satoshi Tadokoro
This e-book is the 5th reputable archival ebook dedicated to RoboCup. It files the achievements offered on the fifth robotic international Cup football video games and meetings held in Seattle, Washington, united states, in August 2001.
The ebook includes the subsequent components: advent, champion groups, problem award finalists, technical papers, poster shows, and group descriptions (arranged in line with a variety of leagues).
This booklet is necessary examining for the swiftly transforming into RoboCup neighborhood in addition to a useful resource of references and idea for R&D pros drawn to multi-agent structures, allotted synthetic intelligence, and clever robotics.
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Extra info for RoboCup 2001: Robot Soccer World Cup V
Another point to recognize is that most of time dissidence in planning does not lead to incoherency in execution. Most of the time dissidence is about whether a player should mark an attacker in the position near a turning point or stay at the formation point, which is hard to judge but scarcely aﬀects the performance. For over 95 percent of the time the team acts uniformly despites of dissidence in 77 percent of the time, which shows that our method has perfectly reached its design goal. In RoboCup 2001, Tsinghuaeolus won the championship, scoring 90 goals, while conceding only 1 goal.
The Interference operator is not used here. There is an alternative where block and press are set as interference instead of mutex, providing a diﬀerent defense strategy. Since either is ok, we do not discuss it further. After decomposing a defense task into defending against each one of the attackers and staying at the basic formation point, arrangements are generated by linking every defender with every subtask. Then, the procedure goes to the evaluation of individual utilities. We deﬁned one evaluation function for each type of action.
The mapping takes place by identifying the triangle which encloses the considered pixel. This triangle can be mapped to a triangle on the field which then is used to interpolate the objects position. For a uniform distribution of the triangles the Delaunay triangulation has been used. Figure 2 shows the generated triangles on the image and the field respectively. The dense occurrence of samples at the bottom of both pictures indicates that more samples have been collected from positions in the vicinity of the robot than from distant positions.