Motion generation from world descriptions: the level of required redundancy

R. Bhatt, A. Meystel
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Abstract

An overview is given of the experimental analysis of motion planning from comparison of two snapshots of the world: initial scene and goal scene. It is commonly believed that from comparison of these two images the researcher can deduce the plan of actions and, eventually, the program of motion (e.g. in robotics). Indeed, in many particular cases the existence of a knowledge inverse operator can be proven. If so, the process of plan generation can be done automatically. The feasibility of solving the problem of automatic plan generation is considered. These questions are addressed by considering several man-chair situations. An effort is made to analyze this process experimentally and to trace the whole set of required computational procedures, as well as the required structure of knowledge representation. It is concluded that difference generation requires a substantial amount of knowledge which is not represented explicitly within the interpreted image description. Supervised learning is one of the possible ways for filling the lists of primitive rules and metarules. However, using redundant thesaural descriptions seems to be more promising.<>
从世界描述生成运动:所需冗余的水平
通过对初始场景和目标场景两种世界快照的比较,综述了运动规划的实验分析。人们普遍认为,从这两幅图像的比较中,研究人员可以推断出行动计划,并最终推断出运动程序(例如在机器人技术中)。实际上,在许多特殊情况下,可以证明知识逆算子的存在性。如果是这样,计划生成过程可以自动完成。考虑了解决方案自动生成问题的可行性。这些问题是通过考虑几个人坐椅子的情况来解决的。通过实验分析了这一过程,并跟踪了整套所需的计算过程,以及所需的知识表示结构。得出的结论是,差分生成需要大量的知识,这些知识在解释后的图像描述中没有明确表示。监督学习是填充原始规则和元规则列表的可能方法之一。然而,使用冗余的自然描述似乎更有希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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