FogROS2 LS: A Location-Independent Fog Robotics Framework for Latency Sensitive ROS2 Applications скачать в хорошем качестве

FogROS2 LS: A Location-Independent Fog Robotics Framework for Latency Sensitive ROS2 Applications

Limiting latency is essential for critical robot applications such as collision avoidance or target tracking and is challenging for Cloud or Fog robotics applications due to net- work congestion and failures. We introduce FogROS2-Latency- Sensitive(LS), a Fog Robotics framework that offers secure, location-independent connections between robots and latency- sensitive robotic services. FogROS2-LS offloads conventional on-board state estimators and feedback controllers to Cloud and Edge compute hardware without modifying the existing application in ROS2. In presence of multiple identical services, it dynamically identifies and transitions to the optimal service deployment that fulfills the application’s latency requirement, thereby empowering robots with restricted on-board computing capacity to safely and efficiently navigate dynamic, human- dense environments. We evaluate FogROS2-LS with two latency sensitive case studies: (1) Collision Avoidance: a robot arm guided by visual feedback from consistent distance estimation and collision checking on Cloud and Edge. FogROS2-LS reduces collision failures by up to 8.5 times by selecting the best available machine, and (2) Target Tracking: FogROS2-LS also enables robust and continuous target following and can recover from network failures. project website: https://sites.google.com/view/fogros-ls/home