Opportunistic intermittent control with safety guarantees for autonomous systems
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Citation (published version)Chao Huang, Shichao Xu, Zhilu Wang, Wenchao Li, Shuyue Lan, Qi Zhu. "Opportunistic Intermittent Control with Safety Guarantees for Autonomous Systems." 57th ACM/EDAC/IEEE ACM/IEEE Design Automation Conference,
Control schemes for autonomous systems are often designed in a way that anticipates the worst case in any situation. At runtime, however, there could exist opportunities to leverage the characteristics of specific environment and operation context for more efficient control. In this work, we develop an online intermittent-control framework that combines formal verification with model-based optimization and deep reinforcement learning to opportunistically skip certain control computation and actuation to save actuation energy and computational resources without compromising system safety. Experiments on an adaptive cruise control system demonstrate that our approach can achieve significant energy and computation savings.
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