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TABLE I REAL DATA SET FOR MOBILE ROBOT NAVIGATION [2]
Table II. Fuzzy inference for velocity control of the mobile robot
2002
Cited by 12
Table 4. Specifications of work assistive mobile robot type II.
Table 1: Sample of mobile mapping and navigation systems Organization System Name Sensors Application
1997
"... In PAGE 3: ... Table1 displays the properties of four mapping and three navigation systems. It is obvious that these mapping systems, which... ..."
Cited by 14
Table 2. Example travel objects extracted from the home page of the Mozilla Foundation and some examples of mapping authoring concepts to mobility concepts. The table should be read in conjunction with Fig. 3 part labelled as A. Please refer to [17] for further information about the mobility concepts.
in Screen readers cannot see (ontology based semantic annotation for visually impaired web travellers
2004
"... In PAGE 6: ... The home page of the Mozilla Foundation can be used to explain some particular concepts in this part of the ontology. Figure 3 (part labelled as A) shows some annota- tions that has been done by using authoring concepts and Table2 provides documenta- tion and hierarchical information about these concepts. 4.... In PAGE 8: ... This new DOM is now in a suitable format for transcoding and the usually complex process of transcoding is dramatically simplified. Table2 shows some sample mappings based on Fig. 3 (part labelled as A) and the following horn clause represents an example mapping rule: NavigationalList # NavigationalList ! DecisionPoint ^ NavigationPoint TextLink ! NavigationPoint ^ TravelMemory NavigationalList ^ TextLink ! DecisionPoint ^ NavigationPoint ^ TravelMemory # DecisionPoint ^ NavigationPoint ^ TravelMemory (1) 14 It also has a proxy server version.... In PAGE 9: ...ions of some transformation heuristics based on our annotations (see Fig. 3). This page is used as an example since it is a typical corporation site and provides good demon- stration of some of the issues concerning the mobility support provided by the page. Figure 3 (see part labelled as A) and Table2 shows the annotations. The page is origi- nally annotated with the authoring concepts (see Sect.... ..."
Cited by 9
Table 1: Robot navigation instances
2005
"... In PAGE 10: ... Table1 summarizes the robot instances. The second column in Table 1 indicates if the instance has a solution.... In PAGE 13: ... Due to the transformation, the number of variables and clauses increases substantially. For example, the Q-ALL SAT instance robot 8 1 has according to Table1 a total of jQj + jXj + jY j = 256 variables, a total of 1521 clauses in R and S, and 925 clauses in R. The corresponding instance in the Q-DIMACS format has 256 + 925 + 1 = 1182 variables and 3211 clauses.... ..."
Cited by 6
Table II tabulates the performance of the robot over 15 configurations, with 10 trials for each configuration. It also shows the localization accuracy of the robot using the learned color map. The robot is able to plan its motion sequence and learn colors in most of the configurations that are designed to be adversarial. The corresponding localization accuracy is comparable to that obtained with the hand-labeled color map (AP BICRD1BN BKCRD1BN BGCSCTCV in CG, CH , and AI).
2006
Cited by 4
Table II tabulates the performance of the robot over 15 configurations, with 10 trials for each configuration. It also shows the localization accuracy of the robot using the learned color map. The robot is able to plan its motion sequence and learn colors in most of the configurations that are designed to be adversarial. The corresponding localization accuracy is comparable to that obtained with the hand-labeled color map (AP BICRD1BN BKCRD1BN BGCSCTCV in CG, CH , and AI).
2006
Cited by 4
Table II also shows the localization accuracy of the robot using the learned color map. The robot is able to plan its motion to learn colors and execute it successfully in most of the configurations that were designed to be adversarial. The corresponding localization accuracy is comparable to that obtained with the hand-labeled color map (AP BICRD1BN BKCRD1BN BGCSCTCV in CG, CH , and AI).
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