The Role of Compute in Autonomous Aerial Vehicles

TL;DR

This paper explores how onboard computing influences the mission duration and energy efficiency of autonomous aerial vehicles, emphasizing the importance of cyber-physical co-design for optimal robot performance.

Contribution

It introduces a comprehensive analysis of compute's role in UAVs, demonstrates the interconnectedness of cyber and physical processes, and provides MAVBench, an open-source benchmarking toolkit.

Findings

Compute significantly impacts mission-time and energy consumption.

Cyber-physical co-design improves UAV performance.

MAVBench enables systematic evaluation of compute-physical interactions.

Abstract

Autonomous-mobile cyber-physical machines are part of our future. Specifically, unmanned-aerial-vehicles have seen a resurgence in activity with use-cases such as package delivery. These systems face many challenges such as their low-endurance caused by limited onboard-energy, hence, improving the mission-time and energy are of importance. Such improvements traditionally are delivered through better algorithms. But our premise is that more powerful and efficient onboard-compute should also address the problem. This paper investigates how the compute subsystem, in a cyber-physical mobile machine, such as a Micro Aerial Vehicle, impacts mission-time and energy. Specifically, we pose the question as what is the role of computing for cyber-physical mobile robots? We show that compute and motion are tightly intertwined, hence a close examination of cyber and physical processes and their impact on one another is necessary. We show different impact paths through which compute impacts mission-metrics and examine them using analytical models, simulation, and end-to-end benchmarking. To enable similar studies, we open sourced MAVBench, our tool-set consisting of a closed-loop simulator and a benchmark suite. Our investigations show cyber-physical co-design, a methodology where robot's cyber and physical processes/quantities are developed with one another consideration, similar to hardware-software co-design, is necessary for optimal robot design.