Avis: In-Situ Model Checking for Unmanned Aerial Vehicles
@article{Taylor2021AvisIM, title={Avis: In-Situ Model Checking for Unmanned Aerial Vehicles}, author={Max G. Taylor and Haicheng Chen and Feng Qin and Christopher Stewart}, journal={2021 51st Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)}, year={2021}, pages={471-483} }
Control firmware in unmanned aerial vehicles (UAVs) uses sensors to model and manage flight operations, from takeoff to landing to flying between waypoints. However, sensors can fail at any time during a flight. If control firmware mishandles sensor failures, UAVs can crash, fly away, or suffer other unsafe conditions. In-situ model checking finds sensor failures that could lead to unsafe conditions by systematically failing sensors. However, the type of sensor failure and its timing within a…
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References
SHOWING 1-10 OF 38 REFERENCES
RVFuzzer: Finding Input Validation Bugs in Robotic Vehicles through Control-Guided Testing
- Computer ScienceUSENIX Security Symposium
- 2019
This paper proposes RVFUZZER, a vetting system for finding input validation bugs in RV control programs through control-guided input mutation, which involves a control instability detector that detects control program misbehavior by observing physical operations of the RV based on the control model.
Detecting Attacks Against Robotic Vehicles: A Control Invariant Approach
- Computer Science, MathematicsCCS
- 2018
This paper presents a novel attack detection framework to identify external, physical attacks against RVs on the fly by deriving and monitoring Control Invariants (CI), and proposes a method to extract such invariants by jointly modeling a vehicle's physical properties, its control algorithm and the laws of physics.
A Fault Detection and Reconfigurable Control Architecture for Unmanned Aerial Vehicles
- Engineering2005 IEEE Aerospace Conference
- 2005
The past decade has seen the development of several reconfigurable flight control strategies for unmanned aerial vehicles. Although the majority of the research is dedicated to fixed wing vehicles,…
Crashing Simulated Planes is Cheap: Can Simulation Detect Robotics Bugs Early?
- Computer Science2018 IEEE 11th International Conference on Software Testing, Verification and Validation (ICST)
- 2018
An empirical study on bugs that have been fixed in the widely used, open-source ArduPilot system finds that the majority of bugs manifest under simple conditions that can be easily reproduced in software-based simulation, and is used to inform a novel framework for testing for bugs in simulation, consistently and reproducibly.
Neural network based sensor validation scheme demonstrated on an unmanned air vehicle (UAV) model
- Computer Science, Engineering2008 47th IEEE Conference on Decision and Control
- 2008
A sensor fault detection and accommodation (SFDA) system, which makes use of analytical redundancy between flight parameters, on a UAV model using a Radial-Basis Function neural network trained online with Extended Minimum Resource Allocating Network (EMRAN) algorithms.
Can You Trust Autonomous Vehicles : Contactless Attacks against Sensors of Self-driving Vehicle
- Computer Science
- 2016
This work investigates sensors whose measurements are used to guide driving, i.e., millimeter-wave radars, ultrasonic sensors, forward-looking cameras, and shows that using o↵-the-shelf hardware, it is able to perform jamming and spoofing attacks, which caused the Tesla's blindness and malfunction, all of which could potentially lead to crashes and impair the safety of self-driving cars.
ML-Based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
- Engineering2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)
- 2019
DriveFI is presented, a machine learning-based fault injection engine, which can mine situations and faults that maximally impact AV safety, as demonstrated on two industry-grade AV technology stacks (from NVIDIA and Baidu).
Simulation of intelligent Unmanned Aerial Vehicle (UAV) For military surveillance
- Computer Science2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS)
- 2013
Application developed in this research has a purpose to simulate condition in war zone for spying the enemy and the result shows that average error for all scenario is only 0.24 meters.
An empirical investigation of fault types in space mission system software
- Computer Science2010 IEEE/IFIP International Conference on Dependable Systems & Networks (DSN)
- 2010
This paper analyzes the faults discovered in the on-board software for 18 JPL/NASA space missions and presents the proportions of the various fault types and study how they have evolved over time.
Practical software model checking via dynamic interface reduction
- Computer ScienceSOSP
- 2011
DeMeter makes software model checking more practical with the following contributions: proposing dynamic interface reduction, a new state-space reduction technique, introducing a framework that enablesynamic interface reduction in an existing model checker with a reasonable amount of effort, and providing the framework with a distributed runtime engine that supports parallel distributed model checking.