Probabilistic Resilience of Dynamic Multi-Robot Systems
Remy Wehbe, Ryan K. Williams
- 发表年份
- 2021
- 引用次数
- 12
摘要
In this letter, we aim to calculate the probability that a dynamic multi-robot system (MRS) satisfies the conditions of (r,s)-robustness, given that robot communication is subject to random failures that can be modeled using a probability distribution. The property of (r,s)-robustness is a topological property used to quantify the resilience of a multi-robot system against misbehaving robots. In the presence of random communication failures, which are typical of real-world deployments, we argue it is important to calculate the probability that an MRS will be resilient at a given time instance. To this end, we begin by enumerating edge sets that represent the conditions of (r,s)-robustness. Then, we use a tree structure known as a binary decision diagram (BDD) to efficiently encode the (r,s)-robustness conditions into a graphical form. This approach allows us to calculate the exact probability of resilience, as well as to derive bounds which are less computationally expensive to compute. To demonstrate the validity of our results, we track the probability of resilience of an MRS performing a collaborative task.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002