RoboRun: A Robot Runtime to Exploit Spatial Heterogeneity
This addresses energy efficiency for autonomous mobile robots, offering a domain-specific incremental improvement by dynamically adapting to environmental heterogeneity.
The paper tackles the challenge of limited onboard energy in autonomous mobile robots by introducing RoboRun, a runtime that dynamically exploits compute-environment synergy, resulting in 4.5X and 4X improvements in mission time and energy, and a 36% reduction in CPU utilization compared to a static design.
The limited onboard energy of autonomous mobile robots poses a tremendous challenge for practical deployment. Hence, efficient computing solutions are imperative. A crucial shortcoming of state-of-the-art computing solutions is that they ignore the robot's operating environment heterogeneity and make static, worst-case assumptions. As this heterogeneity impacts the system's computing payload, an optimal system must dynamically capture these changes in the environment and adjust its computational resources accordingly. This paper introduces RoboRun, a mobile-robot runtime that dynamically exploits the compute-environment synergy to improve performance and energy. We implement RoboRun in the Robot Operating System (ROS) and evaluate it on autonomous drones. We compare RoboRun against a state-of-the-art static design and show 4.5X and 4X improvements in mission time and energy, respectively, as well as a 36% reduction in CPU utilization.