Zimmermann, K. and Freksa, C. (1996). Qualitative spatial reasoning using orientation, distance, path knowledge. Applied Intelligence, 6:49--58.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....data. Exploiting Qualitative Motion Within Qualitative Spatial Reasoning (QSR) see [7] for an overview) navigation in true qualitative terms has been attempted by [32, 10] Orientation knowledge can be seen as dynamic path knowledge and a qualitative concept of motion has been introduced [12]. Using Constraint Logic Programming over finite domains, a Qualitative Navigation Simulator for successful autonomous navigation of a simulated robot through an unknown structured environment has been built [10] More recently, Bennett et al. 2] have explored the expressive power of a ....

C Freksa and K Zimmermann, `Qualitative spatial reasoning using orientation, distance and path knowledge', Applied Intelligence, 6, 49--58, (1996).

.... OMI refers to exactly one object O and has exactly one start moment i s , end moment i e , motion direction # and motion speed v: i om = O##, v#] Several methods on representing spatial relations between objects have been suggested [Clementini et al. 1997,Guesgen, 1989,Schlieder, 1996] and [Zimmermann and Freksa, 1996]. In this approach a spatial relation between two objects is specified through a direction in which the second object is located and the distance between the objects. On a quantitative level a metric distance and an angle in which direction the related second object is placed is calculated. The ....

Zimmermann, K. and Freksa, C. (1996). Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6(1):49--58.

....Koblenz Landau, AI research group Universit atsstr. 1, D 56070 Koblenz, GERMANY stolzen,fruit,murray uni koblenz.de Abstract In many approaches for qualitative spatial reasoning, navigation of an agent in a more or less static environment is considered (e.g. in the double cross calculus [13]) However, in general, the environment is dynamic, which means that both the agent itself and also other objects and agents in the environment may move. Thus, in order to perform spatial reasoning, not only (qualitative) distance and orientation information is needed (as e.g. in [1] but also ....

....some problems can be described quite adequately, e.g. a pressure regulator and a mass spring friction system. However, spatial information is not present in this approach, that is needed for robotic soccer. For further details, the reader is referred to the paper [2] The double cross calculus [13] has been invented to navigate using qualitative spatial information. The double cross calculus uses a set of three points and a set of 15 base relations to achieve this. The three points (the observer, the point where the observer is looking to and a reference object) are related by one of the ....

Kai Zimmermann and Christian Freksa. Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6:49--58, 1996.

....facilities, e.g. dribbling and ball interception. For these actions, almost) no spatial cognition is required. Spatial cognition is the contents of the second layer. For example, players have to recognize when passing the ball is possible or a player is offside. Many approaches (see e.g. [8, 26]) propose purely qualitative reasoning, i.e. disregarding quantitative information after it has been transferred into a qualitative representation. But this may be too inexact and too vague sometimes. Since we use logic as connecting formalism in all layers, we can access low level data at all ....

K. Zimmermann and C. Freksa. Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6:49--58, 1996.

....to exactly one object O and has exactly one start moment i s , end moment i e , motion direction # and motion speed v: i om = O##, v#] i e i s . Several methods on representing spatial relations between objects have been suggested [Clementini et al. 1997,Guesgen, 1989,Schlieder, 1996] and [Zimmermann and Freksa, 1996]. In this approach a spatial relation between two objects is specified through a direction in which the second object is located and the distance between the objects. On a quantitative level a metric distance and an angle in which direction the related second object is placed is calculated. The ....

Zimmermann, K. and Freksa, C. (1996). Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6(1):49--58.

....and Hazarika, 2001b] for an overview) navigation in true qualitative terms has been attempted by [Schlieder, 1993; Escrig and Toledo, 1998] For many applications and especially in case of locomotion, it is not necessary to model position information but only positional change. Consequently, in [Freksa and Zimmermann, 1996] orientation knowledge is seen as dynamic path knowledge and the qualitative concept of motion is introduced. Further, a simple but effective means for representation of a course of motion allowing description at several levels of granularity, abstraction and accuracy suitable for compact storage ....

....of the future of a moving object was suggested by [Musto et al. 1998; Schmid and Wysotzki, 1998] Elsewhere, QSR is seen as a constraint satisfaction problem. As a consequence of this, the treatment of several aspects of space (such as orientation following the Freksa and Zimmermann s approach [Freksa and Zimmermann, 1996] , cardinal directions following Frank s approach [Frank, 1992] and qualitative named distances [Freksa and Zimmermann, 1996] could be integrated into the same spatial model. Using Constraint Logic Programming over finite domains, a Qualitative Navigation Simulator for successful autonomous ....

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C Freksa and K Zimmermann. Qualitative spatial reasoning using orientation, distance and path knowledge. Applied Intelligence, 6:49--58, 1996.

....and projection based (right) models of cardinal directions. front neutral back (a) b) back neutral (c) 1 12 15 5 10 9 4 3 13 8 6 (d) 2 11 7 A B A B B A A B front 14 right left straight Fig. 3. The partition of the universe of 2D positions on which is based the relative orientation calculus in [9, 23]. east, south east, south, south west, west, north west, or equal. Each of the two models can thus be seen as a binary RA, with nine atoms. Both use a global, west east southnorth, reference frame. We focus our attention on the projection based model (Figure 2(right) which has been assessed as ....

....cognitively more adequate [7, 8] cognitive adequacy of spatial orientation models is discussed in [9, 10] 3. 2 Freksa s relative orientation calculus A well known model of relative orientation of 2D points is the calculus de ned by Freksa [9] and developed further by Zimmermann and Freksa [23]. The calculus corresponds to a speci c partition, into 15 regions, of the plane, determined by a parent object, say A, and a reference object, say B (Figure 3(d) The partition is based on the following: 1. the left straight right partition of the plane determined by an observer placed at the ....

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K Zimmermann and C Freksa. Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6:49-58, 1996. 20

....works about distance in qualitative spatial reasoning, but mainly dealing with points [ Hernandez et al. 1995; Frank, 1992 ] In this article, we reuse some of the work of Gambarotto [ Gambarotto, 1999 ] that proposes a qualitative representation of distance between regions. Freksa [ Zimmermann and Freksa, 1993 ] studied qualitative orientation in the case of points, Mukerjee and Joe [ Mukerjee and Joe, 1990 ] treated the relative position of a rectangle with respect to another, and Vieu [ Vieu, 1993 ] introduced direction as a primitive. Qualitative shape of regions has been studied by Cohn [ Cohn, ....

Kai Zimmermann and Christian Freksa. Qualitative Spatial Reasoning Using Orientation, Distance, and Path Knowledge. In Workshop on Spatial Reasoning of the International Join Conference on Artificial Intelligence (IJCAI-93). Chambery, France, 1993.

.... is modelled similarly by using another axis orthogonal to the reference axis (see figure 2) With some reference frames, however, front and back are exchanged (see below, in the section on three point localisation) The result is a qualitative distinction, as suggested, for instance, by Freksa [17]. 2 reference direction reference object left right Figure 1. Reference object and reference direction reference direction reference object front back Figure 2. Front back dichotomy To generate spatial expressions, we utilize the simple sector model introduced by Hernandez [5] This ....

K Zimmermann and C Freksa. Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6:49--58, 1996. 7

....what is, for instance, the angular distance of C from B for an observer placed at A In other words, what is the angle determined by the directed (straight) lines (AB) and (AC) Quantitative versus qualitative orientation. QSR models, and particularly QSR models of 2D orientations (see, e.g. [8, 14, 21]) are based on a partition of the universe of values (for this work, the universe of 2D positions) into a nite number of equivalence classes of qualitatively equal values; no distinction is made between values lying in a same equivalence class. The reason for that is that for some applications, ....

.... universe into a nite number of equivalence classes is related to what Habel, for instance, refers to as the niteness density dilemma [11, 12] To illustrate this, I consider the Double Cross calculus of 2D relative orientation de ned by Freksa [8] and developed further by Zimmermann and Freksa [21]. The calculus contains 15 atomic relations, which correspond to the 15 regions of a speci c partition of the plane determined by a parent object, say A, and a reference object, say B (Figure 1(d) The partition is based on the following: 1. the left straight right dichotomy determined by an ....

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K Zimmermann and C Freksa. Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6:49-58, 1996. 32

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Zimmermann, K. and Freksa, C. (1996). Qualitative spatial reasoning using orientation, distance, path knowledge. Applied Intelligence, 6:49--58.

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K Zimmermann and C Freksa. Qualitative spatial reasoning using orientation, distance, and path knowledge. Applied Intelligence, 6:49--58, 1996.

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