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— The simultaneous localisation and map building (SLAM) problem asks if it is possible for an autonomous vehicle to start in an unknown location in an unknown environment and then to incrementally build a map of this environment while simultaneously using this map to compute absolute vehicle location. Starting from the estimation-theoretic foundations of(More)
This paper discusses tim advantages for practical bi :, direclional grammars 6(combirfiug a lexical fbcus with the (}PEG-originated principle of immediate-dominance/line.ar-precedence (I[)/1,P) rule partitioning. It. also outlines an implenlentation approach fbllowing these gafidelines. The approach is inspired by Slot Grammar, with additions including more(More)
Systematic errors in initial substrate concentration (s(0)), product concentration and reaction time give much larger errors in the Michaelis-Menten parameters unless s(0) is treated as an unknown parameter. These errors are difficult to detect because the fitted curve deviates little from the data. The effect of non-enzymic reaction is also examined.
Design of an autonomous vehicle aims at replacing humans in the driving loop. The autonomous vehicle should be able to understand the environment, estimate its location, and make driving decisions based on the known factors. Such a mobile robot observes its world through sensors such as GPS, SONAR, LIDAR, and Camera [1]. It incorporates each sensor data for(More)