Multi-autonomous robot enhanced mobile ad-hoc network under uncertain and vulnerable environment (Conference Presentation)
Ming Feng, Hao Xu · 2020
This paper studies the problem of real-time routing in a multi-autonomous robot enhanced network at the uncertain and vulnerable tactical edge. In practical harsh environment such as a battlefield, the uncertainty of social mobility and complexity of vulnerable environment due to unpredictable physical and cyber-attacks from the enemy would seriously affect the effectiveness and practicality of these emerging network protocols. This paper presents a GT-SaRE-MANET (Game-Theoretic Situation-aware Robot Enhanced Mobile Ad-hoc Network) routing protocol that adopts the online reinforcement learning technique to supervise the mobility of multi-robots as well as handle the uncertainty and potential physical and cyber-attack at the tactical edge. The proposed design can better support the virtual, augmented, and mixed reality technology in the future battlefield.