# Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

## Pages

Bio and research interests of Meriel von Stein.

## DDEnv

End-to-end tool for delta-debugging robotic environments with a semi-known failure distribution.

## Github repo scraper for robotic swarm projects

Scrape github for swarm projects that fit criteria for project maturity and centering around swarm control.

## Rosbag data cleaning and spline interpolation

Find largest common subinterval among publish rates and interpolate values to populate subintervals by data type.

## Implicit Invariants for Relational Data Structures

Meriel von Stein

Robotics utilizes algorithms for control, localization, and navigation that rely heavily on complex data structures such as matrices and graphs. The values of these data structures are the result of interleaved controllers and complex interactions between equations that are difficult to parameterize as they relate to observed behavior. This makes…

## Probabilistic Conditional System Invariant Generation with Bayesian Inference

Meriel von Stein, Sebastian Elbaum, Lu Feng, Shili Sheng

Probabilistic invariants can encode a family of conditional patterns, are generated using Bayesian inference to leverage observed trace data against priors gleaned from previous experience and expert knowledge, and are ranked based on their surprise value and information content. Our studies on two semi-autonomous mobile robotic systems show how the…

## Automated Environment Reduction for Debugging Robotic Systems

Meriel von Stein, Sebastian Elbaum

Complex environments can cause robots to fail. Identifying the key elements of the environment associated with such failures is critical for faster fault isolation and, ultimately, debugging those failures. In this work we present the first automated approach for reducing the environment in which a robot failed. Similar to software…

## Beyond DNN Silo-Testing: Integrating Autonomous System State

Meriel von Stein, David Shriver, Sebastian Elbaum

Adversarial testing tends to focus on DNNs in isolation, to the exclusion of the full system state and system behaviors resulting from sequences of DNN output. In this work we propose a more holistic approach to DNN testing that accounts for the effects of perturbations on the system state. Our…

## PhysCov: Physical Test Coverage for Autonomous Vehicles

Carl Hildebrandt, Meriel von Stein, Sebastian Elbaum

Adequately covering the behaviors of autonomous vehicles ($AV$) is fundamental in their validation. However, quantifying such coverage is challenging as the $AV$s’ behavior is influenced by its physical environment that is often large and highly complex. This work builds on the insights that data sensed by the $AV$ provides a…