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Implicit Invariants for Relational Data Structures
Meriel von SteinRobotics 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… Read more
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Probabilistic Conditional System Invariant Generation with Bayesian Inference
Meriel von Stein, Sebastian Elbaum, Lu Feng, Shili ShengProbabilistic 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… Read more
Automated Environment Reduction for Debugging Robotic Systems
Meriel von Stein, Sebastian ElbaumComplex 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… Read more
Beyond DNN Silo-Testing: Integrating Autonomous System State
Meriel von Stein, David Shriver, Sebastian ElbaumAdversarial 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… Read more
Preparing Software Engineers to Develop Robot Systems
Carl Hildebrandt, Meriel von Stein, Trey Woodlief, Sebastian ElbaumMost undergraduates are not equipped to manage the unique challenges in developing software for modern robots, despite rapid expansion of the field. We here introduce a course we have designed and delivered to better prepare students to develop software for robot systems. It emphasizes the distinctive challenges of software development… Read more
Finding Property Violations through Network Falsification: Challenges, Adaptations and Lessons Learned from OpenPilot
Meriel von Stein, Sebastian ElbaumOpenpilot is an open source system to assist drivers by providing features like automated lane centering and adaptive cruise control. Like most systems for autonomous vehicles, Openpilot relies on a sophisticated deep neural network (DNN) to provide its functionality, one that is susceptible to safety property violations that can lead… Read more