Learning Ground Traversability from Simulations

Mobile ground robots operating on unstructured terrain must predict which areas of the environment they are able to pass in order to plan feasible paths. We address traversability estimation as a heightmap classification problem: we build a convolutional neural network that, given an image representing the heightmap of a terrain patch, predicts whether the robot will be able to traverse such patch from left to right. The classifier is trained for a specific robot model (wheeled, tracked, legged, snake-like) using simulation data on procedurally generated training terrains; the trained classifier can be applied to unseen large heightmaps to yield oriented traversability maps, and then plan traversable paths. We extensively evaluate the approach in simulation on six real-world elevation datasets, and run a real-robot validation in one indoor and one outdoor environment.Comment: Webpage: http://romarcg.xyz/traversability_estimation

Which Way Was I Going? Contextual Retrieval Supports the Disambiguation of Well Learned Overlapping Navigational Routes

Groundbreaking research in animals has demonstrated that the hippocampus contains neurons that distinguish betweenoverlapping navigational trajectories. These hippocampal neurons respond selectively to the context of specific episodes despite interference from overlapping memory representations. The present study used functional magnetic resonanceimaging in humans to examine the role of the hippocampus and related structures when participants need to retrievecontextual information to navigate well learned spatial sequences that share common elements. Participants were trained outside the scanner to navigate through 12 virtual mazes from a ground-level first-person perspective. Six of the 12 mazes shared overlapping components. Overlapping mazes began and ended at distinct locations, but converged in the middle to share some hallways with another maze. Non-overlapping mazes did not share any hallways with any other maze. Successful navigation through the overlapping hallways required the retrieval of contextual information relevant to thecurrent navigational episode. Results revealed greater activation during the successful navigation of the overlapping mazes compared with the non-overlapping mazes in regions typically associated with spatial and episodic memory, including thehippocampus, parahippocampal cortex, and orbitofrontal cortex. When combined with previous research, the current findings suggest that an anatomically integrated system including the hippocampus, parahippocampal cortex, and orbitofrontal cortexis critical for the contextually dependent retrieval of well learned overlapping navigational routes

Space construction system analysis. Part 2: Cost and programmatics

Cost and programmatic elements of the space construction systems analysis study are discussed. The programmatic aspects of the ETVP program define a comprehensive plan for the development of a space platform, the construction system, and the space shuttle operations/logistics requirements. The cost analysis identified significant items of cost on ETVP development, ground, and flight segments, and detailed the items of space construction equipment and operations

Feasible approach for the computer implementation of parametric visual calculating

Thesis (S.M. in Architecture Studies)--Massachusetts Institute of Technology, Dept. of Architecture, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 62-66).Computational design tools in architecture currently fall into two broad categories: Tools for representation and tools for generative design, including scripting. However, both categories address only relatively methodical aspects of designing, and do little to support the design freedom and serendipitous creativity that, for example, is afforded by iterative sketching. Calculating with visual rules provides an explicit notation for such artistic processes of seeing and drawing. Shape grammars have validated this approach by formalizing many existing designs and styles as visual rule-sets. In this way, visual rules store and transfer design knowledge. Visual calculating in a more general sense supports creativity by allowing a designer to apply any rule she wants, and to capriciously see and re-see the design. In contrast to other explicit design methodologies, visual calculating defines a decomposition into parts only after the design is calculated, thus allowing formalization without impeding design freedom. Located at the intersection between design and computation, the computer implementation of visual calculating presents an opportunity for more designerly computational design tools. Since parametric visual calculating affords the largest set of design possibilities, the computer implementation of parametric visual calculating will allow flexible, rule-based design tools that intelligently combine design freedom with computational processing power. In order to compute with shapes, a symbolic representation for shapes is necessary. This thesis examines several symbolic representations for shapes, including graphs. Especially close attention is given to graph-based representations, since graphs are well suited to represent parametric shapes. Based on this analysis, this thesis proposes a new graph for parametric shapes that is clearer, more compact and closer the original formulation of visual calculating than existing approaches, while also strongly supporting design freedom. The thesis provides algorithms and heuristics to construct this "inverted" graph, for connected and unconnected shapes.by Thomas Alois Wortmann.S.M.in Architecture Studie

Functional MRI investigations of overlapping spatial memories and flexible decision-making in humans

Thesis (Ph.D.)--Boston UniversityResearch in rodents and computational modeling work suggest a critical role for the hippocampus in representing overlapping memories. This thesis tested predictions that the hippocampus is important in humans for remembering overlapping spatial events, and that flexible navigation of spatial routes is supported by key prefrontal and striatal structures operating in conjunction with the hippocampus. The three experiments described in this dissertation used functional magnetic resonance imaging (fMRI) in healthy young people to examine brain activity during context-dependent navigation of virtual maze environments. Experiment 1 tested whether humans recruit the hippocampus and orbitofrontal cortex to successfully retrieve well-learned overlapping spatial routes. Participants navigated familiar virtual maze environments during fMRI scanning. Brain activity for flexible retrieval of overlapping spatial memories was contrasted with activity for retrieval of distinct non-overlapping memories. Results demonstrate the hippocampus is more strongly recruited for planning and retrieval of overlapping routes than non-overlapping routes, and the orbitofrontal cortex is recruited specifically for context-dependent navigational decisions. Experiment 2 examined whether the hippocampus, orbitofrontal cortex, and striatum interact cooperatively to support flexible navigation of overlapping routes. Using a functional connectivity analysis of fMRI data, we compared interactions between these structures during virtual navigation of overlapping and non-overlapping mazes. Results demonstrate the hippocampus interacts with the caudate more strongly for navigating overlapping than non-overlapping routes. Both structures cooperate with the orbitofrontal cortex specifically during context-dependent decision points, suggesting the orbitofrontal cortex mediates translation of contextual information into the flexible selection of behavior. Experiment 3 examined whether the hippocampus and caudate contribute to forming context-dependent memories. fMRI activity for learning new virtual mazes which overlap with familiar routes was compared with activity for learning completely distinct routes. Results demonstrate both the hippocampus and caudate are preferentially recruited for learning mazes which overlap with existing route memories. Furthermore, both areas update their responses to familiar route memories which become context-dependent, suggesting complementary roles in both learning and updating overlapping representations. Together, these studies demonstrate that navigational decisions based on overlapping representations rely on a network incorporating hippocampal function with the evaluation and selection of behavior in the prefrontal cortex and striatum

Opportunity, ethnicity, gender, and CPA exam performance

Given the preeminence of the CPA certification as a measure of professional achievement and a critical element to advancement in the profession, as well as the concerns over lack of diversity in the accounting profession (AICPA 2017), a key policy question is how to improve candidates’ performance on the CPA exam. In this paper, we examine the role of educational and environmental (socioeconomic and segregation) factors representing opportunity, as well as gender and ethnicity (as defined by the National Association of State Boards of Accountancy), on the CPA exam performance. To accomplish this, we first document CPA exam performance across various demographic, educational, and environmental factors. We then develop several multivariate models to understand the influence of various educational and environmental factors representing opportunity on the CPA exam performance of these groups. Finally, we springboard from our findings to offer suggestions to educators, professional firms, and CPA societies, to implement new, or modify current, programs to meet the profession’s need for more qualified CPAs and its diversity/inclusion goals