arXiv subjects

Michael Gleicher

Publications and source records attributed to Michael Gleicher.

At least 19 recordsLinked to original sources

arXiv2026

Divided Attention Amplifies the Importance of Expectation-Aligned Visualization Design

Studies have shown that visualization design affects interpretability when visualization interpretation is the user's sole task. However, in real-world settings, users often engage with visualizations while performing concurrent tasks, such as when users simultaneously monitor alerts or respond to messages. Such divided attention may alter how users interpret visualizations, potentially increasing the importance of designs that align with viewer expectations. We investigated this possibility through two experiments comparing visualization interpretation under single-task and dual-task conditions. Specifically, we examined how well-established inferred mappings between color, spatial position, and semantic concepts affect interpretation when users perform a concurrent task, both with unlimited viewing time (Exp. 1) and under limited viewing time (Exp. 2). Our results show that divided attention amplifies the performance gap between expectation-aligned and expectation-violating designs, affecting response time, interpretation accuracy, and the ability to produce a judgment under time constraints. To explain these results, we model the user's decision-making process using a Linear Ballistic Accumulator (LBA) framework. Our findings highlight the increased importance of aligning visualization designs with viewer expectations under divided attention and introduce a process-oriented modeling approach to understanding how expectation and multitasking shape visualization interpretation.

cs.HC↗

arXiv2026

Make the Unhearable Visible: Exploring Visualization for Musical Instrument Practice

We explore the potential of visualization to support musicians in instrument practice through real-time feedback and reflection on their playing. Musicians often struggle to observe the patterns in their playing and interpret them with respect to their goals. Our premise is that these patterns can be made visible with interactive visualization: we can make the unhearable visible. However, understanding the design of such visualizations is challenging: the diversity of needs, including different instruments, skills, musical attributes, and genres, means that any single use case is unlikely to illustrate the broad potential and opportunities. To address this challenge, we conducted a design exploration study where we created and iterated on 33 designs, each focusing on a subset of needs, for example, only one musical skill. Our designs are grounded in our own experience as musicians and the ideas and feedback of 18 musicians with various musical backgrounds and we evaluated them with 13 music learners and teachers. This paper presents the results of our exploration, focusing on a few example designs as instances of possible instrument practice visualizations. From our work, we draw design considerations that contribute to future research and products for visual instrument education.

cs.HC↗

arXiv2025

Efficient Detection of Objects Near a Robot Manipulator via Miniature Time-of-Flight Sensors

We provide a method for detecting and localizing objects near a robot arm using arm-mounted miniature time-of-flight sensors. A key challenge when using arm-mounted sensors is differentiating between the robot itself and external objects in sensor measurements. To address this challenge, we propose a computationally lightweight method which utilizes the raw time-of-flight information captured by many off-the-shelf, low-resolution time-of-flight sensor. We build an empirical model of expected sensor measurements in the presence of the robot alone, and use this model at runtime to detect objects in proximity to the robot. In addition to avoiding robot self-detections in common sensor configurations, the proposed method enables extra flexibility in sensor placement, unlocking configurations which achieve more efficient coverage of a radius around the robot arm. Our method can detect small objects near the arm and localize the position of objects along the length of a robot link to reasonable precision. We evaluate the performance of the method with respect to object type, location, and ambient light level, and identify limiting factors on performance inherent in the measurement principle. The proposed method has potential applications in collision avoidance and in facilitating safe human-robot interaction.

cs.RO↗

arXiv2025

Recovering Parametric Scenes from Very Few Time-of-Flight Pixels

We aim to recover the geometry of 3D parametric scenes using very few depth measurements from low-cost, commercially available time-of-flight sensors. These sensors offer very low spatial resolution (i.e., a single pixel), but image a wide field-of-view per pixel and capture detailed time-of-flight data in the form of time-resolved photon counts. This time-of-flight data encodes rich scene information and thus enables recovery of simple scenes from sparse measurements. We investigate the feasibility of using a distributed set of few measurements (e.g., as few as 15 pixels) to recover the geometry of simple parametric scenes with a strong prior, such as estimating the 6D pose of a known object. To achieve this, we design a method that utilizes both feed-forward prediction to infer scene parameters, and differentiable rendering within an analysis-by-synthesis framework to refine the scene parameter estimate. We develop hardware prototypes and demonstrate that our method effectively recovers object pose given an untextured 3D model in both simulations and controlled real-world captures, and show promising initial results for other parametric scenes. We additionally conduct experiments to explore the limits and capabilities of our imaging solution.

cs.CV↗

arXiv2025

Anchoring and Alignment: Data Factors in Part-to-Whole Visualization

We explore the effects of data and design considerations through the example case of part-to-whole data relationships. Standard part-to-whole representations like pie charts and stacked bar charts make the relationships of parts to the whole explicit. Value estimation in these charts benefits from two perceptual mechanisms: anchoring, where the value is close to a reference value with an easily recognized shape, and alignment where the beginning or end of the shape is aligned with a marker. In an online study, we explore how data and design factors such as value, position, and encoding together impact these effects in making estimations in part-to-whole charts. The results show how salient values and alignment to positions on a scale affect task performance. This demonstrates the need for informed visualization design based around how data properties and design factors affect perceptual mechanisms.

cs.HC↗

arXiv2025

Hierarchically Accelerated Coverage Path Planning for Redundant Manipulators

Many robotic applications, such as sanding, polishing, wiping and sensor scanning, require a manipulator to dexterously cover a surface using its end-effector. In this paper, we provide an efficient and effective coverage path planning approach that leverages a manipulator's redundancy and task tolerances to minimize costs in joint space. We formulate the problem as a Generalized Traveling Salesman Problem and hierarchically streamline the graph size. Our strategy is to identify guide paths that roughly cover the surface and accelerate the computation by solving a sequence of smaller problems. We demonstrate the effectiveness of our method through a simulation experiment and an illustrative demonstration using a physical robot.

cs.RO↗

arXiv2025

Anytime Planning for End-Effector Trajectory Tracking

End-effector trajectory tracking algorithms find joint motions that drive robot manipulators to track reference trajectories. In practical scenarios, anytime algorithms are preferred for their ability to quickly generate initial motions and continuously refine them over time. In this paper, we present an algorithmic framework that adapts common graph-based trajectory tracking algorithms to be anytime and enhances their efficiency and effectiveness. Our key insight is to identify guide paths that approximately track the reference trajectory and strategically bias sampling toward the guide paths. We demonstrate the effectiveness of the proposed framework by restructuring two existing graph-based trajectory tracking algorithms and evaluating the updated algorithms in three experiments.

cs.RO↗

arXiv2025

Augmenting a Large Language Model with a Combination of Text and Visual Data for Conversational Visualization of Global Geospatial Data

We present a method for augmenting a Large Language Model (LLM) with a combination of text and visual data to enable accurate question answering in visualization of scientific data, making conversational visualization possible. LLMs struggle with tasks like visual data interaction, as they lack contextual visual information. We address this problem by merging a text description of a visualization and dataset with snapshots of the visualization. We extract their essential features into a structured text file, highly compact, yet descriptive enough to appropriately augment the LLM with contextual information, without any fine-tuning. This approach can be applied to any visualization that is already finally rendered, as long as it is associated with some textual description.

cs.HC↗

arXiv2024

RSVP for VPSA : A Meta Design Study on Rapid Suggestive Visualization Prototyping for Visual Parameter Space Analysis

Visual Parameter Space Analysis (VPSA) enables domain scientists to explore input-output relationships of computational models. Existing VPSA applications often feature multi-view visualizations designed by visualization experts for a specific scenario, making it hard for domain scientists to adapt them to their problems without professional help. We present RSVP, the Rapid Suggestive Visualization Prototyping system encoding VPSA knowledge to enable domain scientists to prototype custom visualization dashboards tailored to their specific needs. The system implements a task-oriented, multi-view visualization recommendation strategy over a visualization design space optimized for VPSA to guide users in meeting their analytical demands. We derived the VPSA knowledge implemented in the system by conducting an extensive meta design study over the body of work on VPSA. We show how this process can be used to perform a data and task abstraction, extract a common visualization design space, and derive a task-oriented VisRec strategy. User studies indicate that the system is user-friendly and can uncover novel insights.

cs.HC↗

arXiv2024

Using a Distance Sensor to Detect Deviations in a Planar Surface

We investigate methods for determining if a planar surface contains geometric deviations (e.g., protrusions, objects, divots, or cliffs) using only an instantaneous measurement from a miniature optical time-of-flight sensor. The key to our method is to utilize the entirety of information encoded in raw time-of-flight data captured by off-the-shelf distance sensors. We provide an analysis of the problem in which we identify the key ambiguity between geometry and surface photometrics. To overcome this challenging ambiguity, we fit a Gaussian mixture model to a small dataset of planar surface measurements. This model implicitly captures the expected geometry and distribution of photometrics of the planar surface and is used to identify measurements that are likely to contain deviations. We characterize our method on a variety of surfaces and planar deviations across a range of scenarios. We find that our method utilizing raw time-of-flight data outperforms baselines which use only derived distance estimates. We build an example application in which our method enables mobile robot obstacle and cliff avoidance over a wide field-of-view.

cs.RO↗

arXiv2024

Beware of Validation by Eye: Visual Validation of Linear Trends in Scatterplots

Visual validation of regression models in scatterplots is a common practice for assessing model quality, yet its efficacy remains unquantified. We conducted two empirical experiments to investigate individuals' ability to visually validate linear regression models (linear trends) and to examine the impact of common visualization designs on validation quality. The first experiment showed that the level of accuracy for visual estimation of slope (i.e., fitting a line to data) is higher than for visual validation of slope (i.e., accepting a shown line). Notably, we found bias toward slopes that are "too steep" in both cases. This lead to novel insights that participants naturally assessed regression with orthogonal distances between the points and the line (i.e., ODR regression) rather than the common vertical distances (OLS regression). In the second experiment, we investigated whether incorporating common designs for regression visualization (error lines, bounding boxes, and confidence intervals) would improve visual validation. Even though error lines reduced validation bias, results failed to show the desired improvements in accuracy for any design. Overall, our findings suggest caution in using visual model validation for linear trends in scatterplots.

cs.CV↗

arXiv2024

Motion Comparator: Visual Comparison of Robot Motions

Roboticists compare robot motions for tasks such as parameter tuning, troubleshooting, and deciding between possible motions. However, most existing visualization tools are designed for individual motions and lack the features necessary to facilitate robot motion comparison. In this paper, we utilize a rigorous design framework to develop Motion Comparator, a web-based tool that facilitates the comprehension, comparison, and communication of robot motions. Our design process identified roboticists' needs, articulated design challenges, and provided corresponding strategies. Motion Comparator includes several key features such as multi-view coordination, quaternion visualization, time warping, and comparative designs. To demonstrate the applications of Motion Comparator, we discuss four case studies in which our tool is used for motion selection, troubleshooting, parameter tuning, and motion review.

cs.RO↗

arXiv2024

Enhancing Text Corpus Exploration with Post Hoc Explanations and Comparative Design

Text corpus exploration (TCE) spans the range of exploratory search tasks: it goes beyond simple retrieval to include item discovery and learning about the corpus and topic. Systems support TCE with tools such as similarity-based recommendations and embedding-based spatial maps. However, these tools address specific tasks; current systems lack the flexibility to support the range of tasks encountered in practice and the iterative, multiscale, workflows users employ. In this paper, we provide methods that enhance TCE tools with post hoc explanations and multiscale, comparative designs to provide flexible support for user needs. We introduce salience functions as a mechanism to provide post hoc explanations of similarity, recommendations, and spatial placement. This post hoc strategy allows our approach to complement a variety of underlying algorithms; the salience functions provide both exemplar- and feature-based explanations at scales ranging from individual documents through to the entire corpus. These explanations are incorporated into a set of views that operate at multiple scales. The views use design elements that explicitly support comparison to enable flexible integration. Together, these form an approach that provides a flexible toolset that can address a range of tasks. We demonstrate our approach in a prototype system that enables the exploration of corpora of paper abstracts and newspaper archives. Examples illustrate how our approach enables the system to flexibly support a wide range of tasks and workflows that emerge in user scenarios. A user study confirms that researchers are able to use our system to achieve a variety of tasks.

cs.HC↗

arXiv2024

Towards 3D Vision with Low-Cost Single-Photon Cameras

We present a method for reconstructing 3D shape of arbitrary Lambertian objects based on measurements by miniature, energy-efficient, low-cost single-photon cameras. These cameras, operating as time resolved image sensors, illuminate the scene with a very fast pulse of diffuse light and record the shape of that pulse as it returns back from the scene at a high temporal resolution. We propose to model this image formation process, account for its non-idealities, and adapt neural rendering to reconstruct 3D geometry from a set of spatially distributed sensors with known poses. We show that our approach can successfully recover complex 3D shapes from simulated data. We further demonstrate 3D object reconstruction from real-world captures, utilizing measurements from a commodity proximity sensor. Our work draws a connection between image-based modeling and active range scanning and is a step towards 3D vision with single-photon cameras.

cs.CV↗

arXiv2024

A Design Space of Control Coordinate Systems in Telemanipulation

Teleoperation systems map operator commands from an input device into some coordinate frame in the remote environment. This frame, which we call a control coordinate system, should be carefully chosen as it determines how operators should move to get desired robot motions. While specific choices made by individual systems have been described in prior work, a design space, i.e., an abstraction that encapsulates the range of possible options, has not been codified. In this paper, we articulate a design space of control coordinate systems, which can be defined by choosing a direction in the remote environment for each axis of the input device. Our key insight is that there is a small set of meaningful directions in the remote environment. Control coordinate systems in prior works can be organized by the alignments of their axes with these directions and new control coordinate systems can be designed by choosing from these directions. We also provide three design criteria to reason about the suitability of control coordinate systems for various scenarios. To demonstrate the utility of our design space, we use it to organize prior systems and design control coordinate systems for three scenarios that we assess through human-subject experiments. Our results highlight the promise of our design space as a conceptual tool to assist system designers to design control coordinate systems that are effective and intuitive for operators.

cs.RO↗

arXiv2024

IKLink: End-Effector Trajectory Tracking with Minimal Reconfigurations

Many applications require a robot to accurately track reference end-effector trajectories. Certain trajectories may not be tracked as single, continuous paths due to the robot's kinematic constraints or obstacles elsewhere in the environment. In this situation, it becomes necessary to divide the trajectory into shorter segments. Each such division introduces a reconfiguration, in which the robot deviates from the reference trajectory, repositions itself in configuration space, and then resumes task execution. The occurrence of reconfigurations should be minimized because they increase the time and energy usage. In this paper, we present IKLink, a method for finding joint motions to track reference end-effector trajectories while executing minimal reconfigurations. Our graph-based method generates a diverse set of Inverse Kinematics (IK) solutions for every waypoint on the reference trajectory and utilizes a dynamic programming algorithm to find the globally optimal motion by linking the IK solutions. We demonstrate the effectiveness of IKLink through a simulation experiment and an illustrative demonstration using a physical robot.

cs.RO↗

arXiv2024

A System for Human-Robot Teaming through End-User Programming and Shared Autonomy

Many industrial tasks-such as sanding, installing fasteners, and wire harnessing-are difficult to automate due to task complexity and variability. We instead investigate deploying robots in an assistive role for these tasks, where the robot assumes the physical task burden and the skilled worker provides both the high-level task planning and low-level feedback necessary to effectively complete the task. In this article, we describe the development of a system for flexible human-robot teaming that combines state-of-the-art methods in end-user programming and shared autonomy and its implementation in sanding applications. We demonstrate the use of the system in two types of sanding tasks, situated in aircraft manufacturing, that highlight two potential workflows within the human-robot teaming setup. We conclude by discussing challenges and opportunities in human-robot teaming identified during the development, application, and demonstration of our system.

cs.RO↗

arXiv2023

Subjective visualization experiences: impact of visual design and experimental design

In contrast to objectively measurable aspects (such as accuracy, reading speed, or memorability), the subjective experience of visualizations has only recently gained importance, and we have less experience how to measure it. We explore how subjective experience is affected by chart design using multiple experimental methods. We measure the effects of changes in color, orientation, and source annotation on the perceived readability and trustworthiness of simple bar charts. Three different experimental designs (single image rating, forced choice comparison, and semi-structured interviews) provide similar but different results. We find that these subjective experiences are different from what prior work on objective dimensions would predict. Seemingly inconsequential choices, like orientation, have large effects for some methods, indicating that study design alters decision-making strategies. Next to insights into the effect of chart design, we provide methodological insights, such as a suggested need to carefully isolate individual elements in charts to study subjective experiences.

cs.HC↗