Exploiting Trust for Resilient Hypothesis Testing with Malicious Robots
Matthew Cavorsi,Orhan Eren Akgün,Michal Yemini,Andrea J. Goldsmith,Stephanie Gil,Matthew Cavorsi,Orhan Eren Akgün,Michal Yemini,Andrea J. Goldsmith,Stephanie Gil
We develop a resilient binary hypothesis testing frame-work for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations between robots to arrive at tractable, resilient decision making at a centralized Fusion Center (FC) even when i) there exist malicious robots in the network and their number may be larger than the number of legitimate ...
