Collision free path planning algorithms for robot navigation problem

The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.Title from title screen of research.pdf file (viewed on September 29, 2008)Includes bibliographical references.Thesis (M.S.) University of Missouri-Columbia 2007.Dissertations, Academic -- University of Missouri--Columbia -- Electrical engineering.Path planning problem, including maze navigation is a challenging topic in robotics. Indeed, a significant amount of research has been devoted to this problem in recent years. Genetic algorithm is a popular approach that searches for an optimal solution in given set of solutions. Considering via points as genes in a chromosome will provide a number of possible solutions on a grid map of paths. In this case, path distances that each chromosome creates can be regarded as a fitness measure for the corresponding chromosome. In some cases, a solution path passes through an obstacle. Assuming that the shape of an obstacle is a circle, such random solutions can easily be eliminated by setting-up simple equation between a line created by two via points and the obstacle. The ant colony optimization algorithm is another approach to solve this problem. Each ant drops a quantity of artificial pheromone on every point that the ant passes through. This pheromone simply changes the probability that the next ant becomes attracted to a particular grid point. Since each ant will make a decision at every grid point that it encounters, it is possible that an ant may wander around the grid map or may become stuck among local grid points. In order to prevent this phenomena the proposed solution adapted a global attraction term which guides ants to head toward the destination point. This thesis addresses methods of the path finding problem using these two different approaches. Both algorithms are tested and compared in the result section. The experiment results demonstrate that these two methods have a great potential to solve the proposed problem

Multiple Targets Geolocation Using SIFT and Stereo Vision on Airborne Video Sequences

We propose a robust and accurate method for multi-target geo-localization from airborne video. The difference between our approach and other approaches in the literature is fourfold: 1) it does not require gimbal control of the camera or any particular path planning control for the UAV; 2) it can instantaneously geolocate multiple targets even if they were not previously observed by the camera; 3) it does not require a georeferenced terrain database nor an altimeter for estimating the UAV's and the target's altitudes; and 4) it requires only one camera, but it employs a multi-stereo technique using the image sequence for increased accuracy in target geo-location. The only requirements for our approach are: that the intrinsic parameters of the camera be known; that the on board camera be equipped with global positioning system (GPS) and inertial measurement unit (IMU); and that enough feature points can be extracted from the surroundings of the target. Since the first two constraints are easily satisfied, the only real requirement is regarding the feature points. However, as we explain later, this last constraint can also be alleviated if the ground is approximately planar. The result is a method that can reach a few meters of accuracy for an UAV flying at a few hundred meters above the ground. Such performance is demonstrated by computer simulation, in-scale data using a model city, and real airborne video with ground truth

Early childhood preservice teachers' autonomy in constructing personal practical theories of teaching and learning.

In the findings, the differences of four early childhood preservice teachers in the match or mismatch between their philosophy and personal practical theory related to the how preservice teachers have developed their personal practical theories in context. The differences also are an indicator of each student's personal autonomy. How each four preservice teachers interpreted the dilemmas and issues related to their teaching practice and solved them was different. Each of four preservice teachers developed their own definition of autonomy and acted differently in terms of being autonomous. The early childhood preservice teachers believed that the classes in the teacher education program that critically challenged them to examine their pre-existing theories of teaching and learning promoted their autonomy. The possibility of open communication between intern teacher and cooperating teacher may be an important contextual factor in promoting the preservice teachers' critical reflection and autonomous theory-building process. These findings provided many important implications on the teacher education program.This qualitative case study analyzed the four early childhood preservice teachers' autonomy in constructing personal practical theories in teaching and learning. The research questions of this study are: (1) What are the preservice teachers' personal practical theories about teaching and learning? (2) How have preservice teachers developed their personal practical theories in the context of early experience, teacher education program, and intern teaching? (3) What are the factors influencing the preservice teachers' development of autonomy in constructing their personal practical theories of teaching and learning

Effects of Neighborhood Density and Noise on Children's Word Learning

Studies show that words are organized with similarity neighborhoods based on similar sound structure. Some words have many similar sounding words, while others have few. The number of neighbors a word has is called neighborhood density, which is known to influence word learning. Specifically, words with few neighbors are learned more accurately early in training perhaps because these words play a role in triggering the learning of a novel word. In contrast, words with many neighbors are learned more accurately later in training and post training perhaps because these words play a role in the construction of a new lexical representation in long-term memory and in the connection of the newly constructed lexical representation with existing representations (Storkel, Armbrüster, & Hogan, 2006; Storkel, Bontempor, Aschenbrenner, Maekawa, & Lee, 2013; Storkel & Lee, 2011). However, these findings were obtained in a quiet listening condition, providing little information about the effect of the environment where word learning typically takes place. The goal of this study was to examine whether noise alters the effect of neighborhood density on word learning. Seventy-seven typically developing 4- and 5-year-old preschool children were randomly assigned to one of three listening conditions: 0dB, +6dB, and +15dB signal-to-noise ratio (SNR). Sixteen consonant-vowel-consonant nonword-novel object referent pairs were embedded in two stories for training; neighborhood density for the nonwords varied from low to high. Nonword stimuli and audio narrative scripts for stories were digitally mixed with broadband white noise at 0dB, +6dB, and +15dB SNR. Learning was measured using a picture naming task and a referent identification task. Six cycles of story training-measures of learning were completed with two no training points each after the third and sixth measures of learning. Logistic multi-level modeling (MLM) revealed different patterns of word learning depending on the tasks. Only in the naming task, a significant effect of noise and an interaction between noise and neighborhood density were found at +6dB SNR compared to 0dB SNR. Specifically, results showed that (1) word learning was better at 6dB SNR than 0dB SNR; (2) no significant effect of density was found and this non-significance persisted over time. However, the high density advantage started to emerge at +6dB SNR and +15dB SNR; and (3) the difference between +6dB SNR and 0dB SNR was greater as density increased. In addition, in both naming and referent identification tasks, word learning increased over time with significant forgetting of words in the naming task and a trend of memory consolidation in the referent identification when no training was occurred. These results provide the evidence that word learning declines as listening environment worsen. The results indicate that noise hinders children's ability to use lexical representations, which adversely influences the whole process of word learning (i.e., triggering, configuration, and engagement). The results also imply that high density words are more sensitive to listening condition than low density words. In addition, the naming task that requires more detailed lexical representation is more sensitive to noise than the referent identification task

The Effects of Phonotactic Probability and Neighborhood Density on Adults' Word Learning In Noisy Conditions

Purpose: Noisy conditions make auditory processing difficult. This study explores whether noisy conditions impact the effects of phonotactic probability (the likelihood of occurrence of a sound sequence) and neighborhood density (phonological similarity among words) on adults’ word learning. Method: Fifty-eight adults learned nonwords varying in phonotactic probability and neighborhood density in either an unfavorable (0dB Signal-to-Noise Ratio, SNR) or a favorable (+8dB SNR) listening condition. Word learning was assessed in a picture naming task by scoring the proportion of phonemes named correctly. Results: The unfavorable 0dB SNR condition showed a significant interaction between phonotactic probability and neighborhood density in the absence of main effects. Specifically, adults learned more words when phonotactic probability and neighborhood density were both low or both high. The +8dB SNR condition did not show this interaction. These results were inconsistent with those from a prior adult word learning study under quiet listening conditions that showed main effects of word characteristics. Conclusion: As the listening condition worsens, adult word learning benefits from a convergence of phonotactic probability and neighborhood density Clinical implications are discussed for potential populations who experience difficulty with auditory perception or processing making them more vulnerable to noise

The Influence of Word Characteristics on the Vocabulary of Children with Cochlear Implants

This is the author's accepted manuscript. The original publication is available at http://jdsde.oxfordjournals.org/search?fulltext=The+Influence+of+Word+Characteristics+on+the+Vocabulary+or+Children+With+Cochlear+Implants&submit=yes&x=9&y=4The goal of this study was to explore the effects of phonotactic probability, word length, word frequency, and neighborhood density on the words known by children with cochlear implants (CIs) varying in vocabulary outcomes in a retrospective analysis of a subset of data from a longitudinal study of hearing loss. Generalized linear mixed modeling was used to examine the effects of these word characteristics at three time points: pre-implant, post-implant, and longitudinal follow-up. Results showed a robust effect of neighborhood density across group and time, whereas the effect of frequency varied by time. Significant effects of phonotactic probability or word length were not detected. Taken together, these findings suggest that children with CIs may be able to use spoken language structure in a manner similar to their normal hearing counterparts, despite the differences in the quality of the input. The differences in the effects of phonotactic probability and word length imply a difficulty in initiating word learning and limited working memory ability in children with CIs

A Passivity-based Nonlinear Admittance Control with Application to Powered Upper-limb Control under Unknown Environmental Interactions

This paper presents an admittance controller based on the passivity theory for a powered upper-limb exoskeleton robot which is governed by the nonlinear equation of motion. Passivity allows us to include a human operator and environmental interaction in the control loop. The robot interacts with the human operator via F/T sensor and interacts with the environment mainly via end-effectors. Although the environmental interaction cannot be detected by any sensors (hence unknown), passivity allows us to have natural interaction. An analysis shows that the behavior of the actual system mimics that of a nominal model as the control gain goes to infinity, which implies that the proposed approach is an admittance controller. However, because the control gain cannot grow infinitely in practice, the performance limitation according to the achievable control gain is also analyzed. The result of this analysis indicates that the performance in the sense of infinite norm increases linearly with the control gain. In the experiments, the proposed properties were verified using 1 degree-of-freedom testbench, and an actual powered upper-limb exoskeleton was used to lift and maneuver the unknown payload.Comment: Accepted in IEEE/ASME Transactions on Mechatronics (T-MECH