Recognition and prediction of motion situations based on a qualitative motion description

Andrea Miene, Ubbo E Visser, Otthein Herzog

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

High-level online methods become more and more attractive with the increasing abilities of players and teams in the simulation league. As in real soccer, the recognition and prediction of strategies (e.g. opponent's formation), tactics (e.g. wing play, offside traps), and situations (e.g. passing behavior) is important. In 2001, we proposed an approach where spatio-temporal relations between objects are described and interpreted in order to detect some of the above mentioned situations. In this paper we propose an extension of this approach that enables us to both interpret and predict complex situations. It is based on a qualitative description of motion scenes and additional background knowledge. The method is applicable to a variety of situations. Our experiment consists of numerous offside situations in simulation league games. We discuss the results in detail and conclude that this approach is valuable for future use because it is (a) possible to use the method in real-time, (b) we can predict situations giving us the option to refine agents actions in a game, and (c) it is domain independent in general.

Original languageEnglish (US)
Title of host publicationLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
PublisherSpringer Verlag
Pages77-88
Number of pages12
Volume3020
ISBN (Print)3540224432, 9783540224433
StatePublished - 2004
Externally publishedYes
Event7th Robot World Cup Soccer and Rescue Competitions and Conferences, RoboCup 2003 - Padua, Italy
Duration: Jul 2 2003Jul 11 2003

Other

Other7th Robot World Cup Soccer and Rescue Competitions and Conferences, RoboCup 2003
CountryItaly
CityPadua
Period7/2/037/11/03

Fingerprint

Motion
Prediction
Game
Predict
Experiments
Trap
Simulation
Real-time
Experiment
Knowledge
Object
Strategy
Background

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Miene, A., Visser, U. E., & Herzog, O. (2004). Recognition and prediction of motion situations based on a qualitative motion description. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3020, pp. 77-88). Springer Verlag.

Recognition and prediction of motion situations based on a qualitative motion description. / Miene, Andrea; Visser, Ubbo E; Herzog, Otthein.

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). Vol. 3020 Springer Verlag, 2004. p. 77-88.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Miene, A, Visser, UE & Herzog, O 2004, Recognition and prediction of motion situations based on a qualitative motion description. in Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). vol. 3020, Springer Verlag, pp. 77-88, 7th Robot World Cup Soccer and Rescue Competitions and Conferences, RoboCup 2003, Padua, Italy, 7/2/03.
Miene A, Visser UE, Herzog O. Recognition and prediction of motion situations based on a qualitative motion description. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). Vol. 3020. Springer Verlag. 2004. p. 77-88
Miene, Andrea ; Visser, Ubbo E ; Herzog, Otthein. / Recognition and prediction of motion situations based on a qualitative motion description. Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). Vol. 3020 Springer Verlag, 2004. pp. 77-88
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