Spatial Concept Acquisition Research Articles

Semantic Mapping Based on Spatial Concepts for Grounding Words Related to Places in Daily Environments.

An autonomous robot performing tasks in a human environment needs to recognize semantic information about places. Semantic mapping is a task in which suitable semantic information is assigned to an environmental map so that a robot can communicate with people and appropriately perform tasks requested by its users. We propose a novel statistical semantic mapping method called SpCoMapping, which integrates probabilistic spatial concept acquisition based on multimodal sensor information and a Markov random field applied for learning the arbitrary shape of a place on a map.SpCoMapping can connect multiple words to a place in a semantic mapping process using user utterances without pre-setting the list of place names. We also develop a nonparametric Bayesian extension of SpCoMapping that can automatically estimate an adequate number of categories. In the experiment in the simulation environments, we showed that the proposed method generated better semantic maps than previous semantic mapping methods; our semantic maps have categories and shapes similar to the ground truth provided by the user. In addition, we showed that SpCoMapping could generate appropriate semantic maps in a real-world environment.

Unsupervised spatial lexical acquisition by updating a language model with place clues

Abstract This paper describes how to achieve highly accurate unsupervised spatial lexical acquisition from speech-recognition results including phoneme recognition errors. In most research into lexical acquisition, the robot has no pre-existing lexical knowledge. The robot acquires sequences of some phonemes as words from continuous speech signals. In a previous study, we proposed a nonparametric Bayesian spatial concept acquisition method (SpCoA) that integrates the robot’s position and words obtained by unsupervised word segmentation from uncertain syllable recognition results. However, SpCoA has a very critical problem to be solved in lexical acquisition; the boundaries of word segmentation are incorrect in many cases because of many phoneme recognition errors. Therefore, we propose an unsupervised machine learning method (SpCoA++) for the robust lexical acquisition of novel words relating to places visited by the robot. The proposed SpCoA++ method performs an iterative estimation of learning spatial concepts and updating a language model using place information. SpCoA++ can select a candidate including many words that better represent places from multiple word-segmentation results by maximizing the mutual information between segmented words and spatial concepts. The experimental results demonstrate a significant improvement of the phoneme accuracy rate of learned words relating to place in the proposed method by word-segmentation results based on place information, in comparison to the conventional methods. We indicate that the proposed method enables the robot to acquire words from speech signals more accurately, and improves the estimation accuracy of the spatial concepts.

The Effects of Dora the Explorer on Preschool Children's Spatial Concept Acquisition and Spatial Ability

The purpose of this research is to investigate the effects of Dora the Explorer cartoon on the spatial concept acquisitions and spatial abilities of the preschool children. The study was carried out with 80, 60-71 month old children attending preschools. Post-test only control group model is used in the research in order to identify the existing phenomena in a controlled manner. “The Bracken Basic Concept Scale, Third Edition: Receptive (BBCSIII:R) Form Direction/Position Subscale” and two different “Spatial Ability Games” were used to assess children’s spatial concept acquisitions and spatial abilities. Independent sample t-test was used in order to compare the average of post-test scores of the children in the experimental and control groups. According to the findings, it is found that there is meaningful difference between scores of post-tests of direction/position subscale and spatial ability games score. Comparing the scores of post-test of direction/position subscale and spatial ability games of experimental and control groups, it was found that there was a meaningful differentiation in favor of experimental group.

Spatial Concept Acquisition for a Mobile Robot that Integrates Self-Localization and Unsupervised Word Discovery from Spoken Sentences

In this paper, we propose a novel unsupervised learning method for the lexical acquisition of words related to places visited by robots, from human continuous speech signals. We address the problem of learning novel words by a robot that has no prior knowledge of these words except for a primitive acoustic model. Further, we propose a method that allows a robot to effectively use the learned words and their meanings for self-localization tasks. The proposed method is nonparametric Bayesian spatial concept acquisition method (SpCoA) that integrates the generative model for self-localization and the unsupervised word segmentation in uttered sentences via latent variables related to the spatial concept. We implemented the proposed method SpCoA on SIGVerse, which is a simulation environment, and TurtleBot2, which is a mobile robot in a real environment. Further, we conducted experiments for evaluating the performance of SpCoA. The experimental results showed that SpCoA enabled the robot to acquire the names of places from speech sentences. They also revealed that the robot could effectively utilize the acquired spatial concepts and reduce the uncertainty in self-localization.

The Need for Motor Development Programs for Visually Impaired Preschoolers

Visually impaired children have difficulty acquiring spatial orientation concepts necessary for proficient locomotive movements and independent mobility. The majority of past research on remedying spatial deficits has focused on older visually impaired individuals. It is the purpose of this paper to advocate the development of movement programs for preschool visually impaired children in order to compensate for their orientation deficits. Skills necessary for acquisition of spatial concepts should be taught through movement programs at an early age in the normal developmental sequence instead of attempting to remedy deficits at a later age.