Avalon: Building an Operating System for Robotcenter
This addresses the challenge of enabling efficient and concurrent multi-user access to heterogeneous robot resources, which is incremental by adapting datacenter OS principles to robotics.
The paper tackles the problem of managing hundreds of heterogeneous robots in a shared robotcenter for multiple users by proposing Avalon, a robot operating system with a two-level scheduling scheme, which integrates fine-grained resource classification, location-based allocation, and cloud offloading, and is evaluated in simulated and real-world environments.
This paper envisions a scenario that hundreds of heterogeneous robots form a robotcenter which can be shared by multiple users and used like a single powerful robot to perform complex tasks. However, current multi-robot systems are either unable to manage heterogeneous robots or unable to support multiple concurrent users. Inspired by the design of modern datacenter OSes, we propose Avalon, a robot operating system with two-level scheduling scheme which is widely adopted in datacenters for Internet services and cloud computing. Specifically, Avalon integrates three important features together: (1) Instead of allocating a whole robot, Avalon classifies fine-grained robot resources into three categories to distinguish which fine-grained resources can be shared by multi-robot frameworks simultaneously. (2) Avalon adopts a location based resource allocation policy to substantially reduce scheduling overhead. (3) Avalon enables robots to offload computation intensive tasks to the clouds.We have implemented and evaluated Avalon on robots on both simulated environments and real world.