John Harwell

AAMAS Conference 2023 Conference Paper

Provably Manipulable 3D Structures using Graph Theory

• John Harwell
• London Lowmanstone
• Maria Gini

We identify barriers to a broader application of multi-robot systems to construction and deconstruction tasks, which represent important real-world problems, such as repairing critical infrastructure of roads and levies after a disaster. We frame these tasks as instances of the parallel bricklayer problem, where independent agents must coordinate to concurrently manipulate aspects of a 3D environment without deadlocks. We extract desirable properties of graphs representing natural 3D structures and sketch a graphical representation to model and reason about structures composed of discrete cuboid blocks. We present a sample algorithm sketch for a non-trivial structure utilizing our model.

ICRA Conference 2023 Conference Paper

SIERRA: A Modular Framework for Accelerating Research and Improving Reproducibility

• John Harwell
• Maria L. Gini

We present SIERRA, a novel framework for accelerating development and improving reproducibility of results in robotics research. SIERRA accelerates research by automating the process of generating experiments from queries over independent variables, executing experiments, and processing the results to generate deliverables such as graphs and videos. It shifts the paradigm for testing hypotheses from procedural (“Do these steps to answer the query”) to declarative (“Here is the query to test—GO! ”), reducing the burden on researchers. It employs a modular architecture enabling easy customization and extension for the needs of individual researchers, thereby eliminating manual configuration and processing via throw-away scripts. SIERRA improves reproducibility of research by providing automation independent of the execution environment (HPC hardware, real robots, etc.) and targeted platform (simulator, real robots, etc.). This enables exact experiment replication, up to the limit of the execution environment and platform, as well as making it easy for researchers to test hypotheses in different computational environments. Though SIERRA is targeted at robotics research, its design makes it extendable to other fields.

AAMAS Conference 2022 Conference Paper

SIERRA: A Modular Framework for Research Automation

• John Harwell
• London Lowmanstone
• Maria Gini

Modern intelligent systems researchers form hypotheses about system behavior and then run experiments using one or more independent variables to test their hypotheses. We present SIERRA, a novel framework structured around that idea for accelerating research developments and improving reproducibility of results. SIERRA makes it easy to quickly specify the independent variable(s) for an experiment, generate experimental inputs, automatically run the experiment, and process the results to generate deliverables such as graphs and videos. SIERRA provides reproducible automation independent of the execution environment (HPC hardware, real robots, etc.) and targeted platform (arbitrary simulator or real robots), enabling exact experiment replication (up to the limit of the execution environment and platform). It employs a deeply modular approach that allows easy customization and extension of automation for the needs of individual researchers, thereby eliminating manual experiment configuration and result processing via throw-away scripts.

IJCAI Conference 2019 Conference Paper

A Unified Mathematical Approach for Foraging and Construction Systems in a 1, 000, 000 Robot Swarm

• John Harwell

Automation in construction is possible with systems designed using the swarm robotic principles of scalability, flexibility, robustness, and emergence. We derive quantitative measurements of these principles in 10, 000 robot swarms as a first step in achieving this goal. We summarize our recent task allocation work in the context of an object gathering task and demonstrate its feasibility in the context of automated construction tasks. We present a trajectory to extend our current task allocation methodology using stochastic processes in order to present a unified approach to task allocation in swarm-robotic construction

IJCAI Conference 2019 Conference Paper

Swarm Engineering Through Quantitative Measurement of Swarm Robotic Principles in a 10, 000 Robot Swarm

• John Harwell
• Maria Gini

When designing swarm-robotic systems, system- atic comparison of algorithms from different do- mains is necessary to determine which is capa- ble of scaling up to handle the target problem size and target operating conditions. We propose a set of quantitative metrics for scalability, flexibility, and emergence which are capable of addressing these needs during the system design process. We demonstrate the applicability of our proposed met- rics as a design tool by solving a large object gath- ering problem in temporally varying operating con- ditions using iterative hypothesis evaluation. We provide experimental results obtained in simulation for swarms of over 10, 000 robots.

YNIMG Journal 2017 Journal Article

The Brain Analysis Library of Spatial maps and Atlases (BALSA) database

• David C. Van Essen
• John Smith
• Matthew F. Glasser
• Jennifer Elam
• Chad J. Donahue
• Donna L. Dierker
• Erin K. Reid
• Timothy Coalson

We report on a new neuroimaging database, BALSA, that is a repository for extensively analyzed neuroimaging datasets from humans and nonhuman primates. BALSA is organized into two distinct sections. BALSA Reference is a curated repository of reference data accurately mapped to brain atlas surfaces and volumes, including various types of anatomically and functionally derived spatial maps as well as brain connectivity. BALSA Studies is a repository of extensively analyzed neuroimaging and neuroanatomical datasets associated with specific published studies, as voluntarily submitted by authors. It is particularly well suited for sharing of neuroimaging data as displayed in published figures. Uploading and downloading of data to BALSA involves ‘scene’ files that replicate how datasets appear in Connectome Workbench visualization software. Altogether, BALSA offers efficient access to richly informative datasets that are related to but transcend the images available in scientific publications.

YNIMG Journal 2016 Journal Article

Comparison of cortical folding measures for evaluation of developing human brain

• Joshua S. Shimony
• Christopher D. Smyser
• Graham Wideman
• Dimitrios Alexopoulos
• Jason Hill
• John Harwell
• Donna Dierker
• David C. Van Essen

We evaluated 22 measures of cortical folding, 20 derived from local curvature (curvature-based measures) and two based on other features (sulcal depth and gyrification index), for their capacity to distinguish between normal and aberrant cortical development. Cortical surfaces were reconstructed from 12 term-born control and 63 prematurely-born infants. Preterm infants underwent 2–4 MR imaging sessions between 27 and 42weeks postmenstrual age (PMA). Term infants underwent a single MR imaging session during the first postnatal week. Preterm infants were divided into two groups. One group (38 infants) had no/minimal abnormalities on qualitative assessment of conventional MR images. The second group (25 infants) consisted of infants with injury on conventional MRI at term equivalent PMA. For both preterm infant groups, all folding measures increased or decreased monotonically with increasing PMA, but only sulcal depth and gyrification index differentiated preterm infants with brain injury from those without. We also compared scans obtained at term equivalent PMA (36–42weeks) for all three groups. No curvature-based measured distinguished between the groups, whereas sulcal depth distinguished term control from injured preterm infants and gyrification index distinguished all three groups. When incorporating total cerebral volume into the statistical model, sulcal depth no longer distinguished between the groups, though gyrification index distinguished between all three groups and positive shape index distinguished between the term control and uninjured preterm groups. We also analyzed folding measures averaged over brain lobes separately. These results demonstrated similar patterns to those obtained from the whole brain analyses. Overall, though the curvature-based measures changed during this period of rapid cerebral development, they were not sensitive for detecting the differences in folding associated with brain injury and/or preterm birth. In contrast, gyrification index was effective in differentiating these groups.

YNIMG Journal 2013 Journal Article

Human Connectome Project informatics: Quality control, database services, and data visualization

• Daniel S. Marcus
• Michael P. Harms
• Abraham Z. Snyder
• Mark Jenkinson
• J. Anthony Wilson
• Matthew F. Glasser
• Deanna M. Barch
• Kevin A. Archie

The Human Connectome Project (HCP) has developed protocols, standard operating and quality control procedures, and a suite of informatics tools to enable high throughput data collection, data sharing, automated data processing and analysis, and data mining and visualization. Quality control procedures include methods to maintain data collection consistency over time, to measure head motion, and to establish quantitative modality-specific overall quality assessments. Database services developed as customizations of the XNAT imaging informatics platform support both internal daily operations and open access data sharing. The Connectome Workbench visualization environment enables user interaction with HCP data and is increasingly integrated with the HCP's database services. Here we describe the current state of these procedures and tools and their application in the ongoing HCP study.

YNIMG Journal 2001 Journal Article

Integrated software for surface-based analyses of cerebral cortex

• John Harwell
• David Van Essen
• Donna Hanlon
• James Dickson