Approximate Probabilistic Security for Networked Multi-Robot Systems
Title | Approximate Probabilistic Security for Networked Multi-Robot Systems |
Publication Type | Conference Paper |
Year of Publication | 2019 |
Authors | Wehbe, R., Williams, R. K. |
Conference Name | 2019 International Conference on Robotics and Automation (ICRA) |
Date Published | May 2019 |
Publisher | IEEE |
ISBN Number | 978-1-5386-6027-0 |
Keywords | approximate probabilistic security, binary decision diagrams, Boolean functions, combinatorial optimization problem, computational complexity, control system security, disjoint path sets, exact probability, graph theory, Human Behavior, human factors, left invertiblility, lower bound estimate, MRS, multi-robot systems, multipoint optimization, networked control systems, networked multirobot systems, Observers, online optimization, optimal subset, optimisation, policy-based governance, Probabilistic logic, probability, pubcrawl, resilience, Resiliency, robot operating systems, Robot sensing systems, security |
Abstract | In this paper, we formulate a combinatorial optimization problem that aims to maximize the accuracy of a lower bound estimate of the probability of security of a multi-robot system (MRS), while minimizing the computational complexity involved in its calculation. Security of an MRS is defined using the well-known control theoretic notion of left invertiblility, and the probability of security of an MRS can be calculated using binary decision diagrams (BDDs). The complexity of a BDD depends on the number of disjoint path sets considered during its construction. Taking into account all possible disjoint paths results in an exact probability of security, however, selecting an optimal subset of disjoint paths leads to a good estimate of the probability while significantly reducing computation. To deal with the dynamic nature of MRSs, we introduce two methods: (1) multi-point optimization, a technique that requires some a priori knowledge of the topology of the MRS over time, and (2) online optimization, a technique that does not require a priori knowledge, but must construct BDDs while the MRS is operating. Finally, our approach is validated on an MRS performing a rendezvous objective while exchanging information according to a noisy state agreement process. |
URL | https://ieeexplore.ieee.org/document/8794232 |
DOI | 10.1109/ICRA.2019.8794232 |
Citation Key | wehbe_approximate_2019 |
- multipoint optimization
- security
- Robot sensing systems
- robot operating systems
- Resiliency
- resilience
- pubcrawl
- probability
- Probabilistic logic
- policy-based governance
- optimisation
- optimal subset
- online optimization
- Observers
- networked multirobot systems
- networked control systems
- approximate probabilistic security
- multi-robot systems
- MRS
- lower bound estimate
- left invertiblility
- Human Factors
- Human behavior
- graph theory
- exact probability
- disjoint path sets
- control system security
- computational complexity
- combinatorial optimization problem
- Boolean functions
- binary decision diagrams