MulBERRY: Enabling Bit-Error Robustness for Energy-Efficient Multi-Agent Autonomous Systems
Zishen Wan, Nandhini Chandramoorthy, Karthik Swaminathan, Pin‐Yu Chen, Kshitij Bhardwaj, Vijay Janapa Reddi, Arijit Raychowdhury · 2024
The adoption of autonomous swarms, consisting of a multitude of unmanned aerial vehicles (UAVs), operating in a collaborative manner, has become prevalent in mainstream application domains for both military and civilian purposes. These swarms are expected to collaboratively carry out navigation tasks and employ complex reinforcement learning (RL) models within the stringent onboard size, weight, and power constraints. While techniques such as reducing onboard operating voltage can improve the energy efficiency of both computation and flight missions, they can lead to on-chip bit failures that are detrimental to mission safety and performance.